{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 16 - 断点回归\n",
    "\n",
    "\n",
    "我们不会停下来想太多，但大自然的平滑程度令人印象深刻。没有先发芽就不能种树，不能从一个地方传送到另一个地方，伤口需要时间来愈合。即使在社交领域，顺畅似乎也是常态。您无法在一天内发展业务，建立财富需要一致性和辛勤工作，并且需要数年才能了解线性回归的工作原理。在正常情况下，大自然非常有凝聚力，不会跳来跳去。\n",
    "\n",
    "\n",
    "> 当智慧和动物的灵魂被抱在一起时，它们就不会分离。\n",
    "\n",
    "\\-道德经，老子。\n",
    "\n",
    "这意味着**当我们确实看到跳跃和尖峰时，它们可能是人为的**并且通常是人为的情况。这些事件通常伴随着对正常事物方式的反事实：如果发生了一件奇怪的事情，这让我们对如果大自然以不同的方式工作会发生什么有了一些了解。探索这些人工跳跃是回归不连续设计的核心。\n",
    "\n",
    "![img](./data/img/rdd/smooth.png)\n",
    "\n",
    "基本设置是这样的。假设您有一个干预变量 \\\\(T\\\\) 和潜在结果 \\\\(Y_0\\\\) 和 \\\\(Y_1\\\\)。处理 T 是观察到的运行变量 \\\\(R\\\\) 的不连续函数，使得\n",
    "\n",
    "$\n",
    "D_i = \\mathcal{1}\\{R_i>c\\}\n",
    "$\n",
    "\n",
    "换句话说，这就是说当 \\\\(R\\\\) 低于阈值 \\\\(c\\\\) 时处理为零，否则为 1。这意味着我们可以在 \\\\(R>c\\\\) 时观察 \\\\(Y_1\\\\) 和在 \\\\(R<c\\\\) 时观察 \\\\(Y_0\\\\)。为了解决这个问题，请将潜在结果视为我们无法完全观察到的 2 个函数。 \\\\(Y_0(R)\\\\) 和 \\\\(Y_1(R)\\\\) 都在那里，我们只是看不到。阈值充当一个开关，让我们可以看到其中一个或另一个功能，但不能同时看到两者，就像下图一样：\n",
    "\n",
    "![img](./data/img/rdd/rdd.png)\n",
    "\n",
    "断点回归的想法是比较刚好高于和低于阈值的结果，以确定阈值处的干预效果。这被称为 **sharp RD** 设计，因为在阈值处获得干预的概率从 0 跳到 1，但我们也可以考虑 **fuzzy RD** 设计，其中概率也会跳跃，但是是一种不那么剧烈的方式。\n",
    "\n",
    "## 酒精会杀死你吗？\n",
    "\n",
    "一个非常相关的公共政策问题是最低饮酒年龄应该是多少。大多数国家，包括巴西，将其设定为 18 岁，但在美国（大多数州），目前是 21 岁。那么，美国是否过于谨慎，应该降低最低饮酒年龄？还是其他国家应该提高法定饮酒年龄？\n",
    "\n",
    "看待这个问题的一种方法是从 [死亡率的角度 (Carpenter and Dobkin, 2009)](https://www.aeaweb.org/articles?id=10.1257/app.1.1.164)。从公共政策的角度来看，人们可以争辩说我们应该尽可能地降低死亡率。如果饮酒会大幅增加死亡率，我们应该避免降低最低饮酒年龄。这与降低因饮酒导致的死亡人数的目标是一致的。\n",
    "\n",
    "为了估计酒精对死亡的影响，我们可以利用法定饮酒年龄本质上是施加了不连续性这一事实。在美国，21 岁以下的人不喝酒（或少喝酒），而 21 岁以上的人则喝酒。这意味着饮酒的概率在 21 岁时会增加，这是我们可以用 RDD 来探索的。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from matplotlib import style\n",
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns\n",
    "import statsmodels.formula.api as smf\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "style.use(\"fivethirtyeight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "为此，我们可以获取一些按年龄汇总的死亡率数据。 每行是一组人的平均年龄和按照所有原因（`all`）、移动车辆事故（`mva`）和自杀（`suicide`）分别统计的平均死亡率。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>agecell</th>\n",
       "      <th>all</th>\n",
       "      <th>mva</th>\n",
       "      <th>suicide</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19.068493</td>\n",
       "      <td>92.825400</td>\n",
       "      <td>35.829327</td>\n",
       "      <td>11.203714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19.150684</td>\n",
       "      <td>95.100740</td>\n",
       "      <td>35.639256</td>\n",
       "      <td>12.193368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19.232876</td>\n",
       "      <td>92.144295</td>\n",
       "      <td>34.205650</td>\n",
       "      <td>11.715812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19.315070</td>\n",
       "      <td>88.427760</td>\n",
       "      <td>32.278957</td>\n",
       "      <td>11.275010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19.397260</td>\n",
       "      <td>88.704940</td>\n",
       "      <td>32.650967</td>\n",
       "      <td>10.984314</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     agecell        all        mva    suicide\n",
       "0  19.068493  92.825400  35.829327  11.203714\n",
       "1  19.150684  95.100740  35.639256  12.193368\n",
       "2  19.232876  92.144295  34.205650  11.715812\n",
       "3  19.315070  88.427760  32.278957  11.275010\n",
       "4  19.397260  88.704940  32.650967  10.984314"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "drinking = pd.read_csv(\"./data/drinking.csv\")\n",
    "drinking.head()[[\"agecell\", \"all\", \"mva\", \"suicide\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "为了提升视觉效果（以及我们将在后面看到的另一个重要原因）我们将以阈值 21为中点将 `agecell`这个变量去中心化。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "drinking[\"agecell\"] -= 21"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果我们将多个结果变量（`all`、`mva`、`suicide`）与 x 轴上的对应变量一起绘制，图形会提示我们，当我们越过法定饮酒年龄时，死亡率会出现一定跳跃。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "ax = plt.subplot(3,1,1)\n",
    "drinking.plot.scatter(x=\"agecell\", y=\"all\", ax=ax)\n",
    "plt.title(\"Death Cause by Age (Centered at 0)\")\n",
    "\n",
    "ax = plt.subplot(3,1,2, sharex=ax)\n",
    "drinking.plot.scatter(x=\"agecell\", y=\"mva\", ax=ax)\n",
    "\n",
    "ax = plt.subplot(3,1,3, sharex=ax)\n",
    "drinking.plot.scatter(x=\"agecell\", y=\"suicide\", ax=ax);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "有一些线索，但我们需要的不止这些。在阈值周围，饮酒对死亡率的影响究竟是什么？该估计的标准误差是多少？\n",
    "\n",
    "## RDD 估计\n",
    "\n",
    "RDD 依赖的关键假设是阈值处潜在结果的平滑性。用比较正式地表述来说，当运行变量从右侧和左侧接近阈值时，潜在结果的极限应该是相同的。\n",
    "\n",
    "$$\n",
    "\\lim_{r \\to c^-} E[Y_{ti}|R_i=r] = \\lim_{r \\to c^+} E[Y_{ti}|R_i=r]\n",
    "$$\n",
    "\n",
    "如果这是真的，我们可以在阈值处找到因果关系\n",
    "\n",
    "$$\n",
    "\\begin{align}\n",
    "\\lim_{r \\to c^+} E[Y_{ti}|R_i=r] - \\lim_{r \\to c^-} E[Y_{ti}|R_i=r]=&\\lim_{r \\to c^+} E[Y_{1i}|R_i=r] - \\lim_{r \\to c^-} E[Y_{0i}|R_i=r] \\\\\n",
    "=& E[Y_{1i}|R_i=r] - E[Y_{0i}|R_i=r] \\\\\n",
    "=& E[Y_{1i} - Y_{0i}|R_i=r]\n",
    "\\end{align}\n",
    "$$\n",
    "\n",
    "从其本身意义来说，这是一种局部平均干预效果（LATE），因为我们只能在阈值处知道它。在这种情况下，我们可以将 RDD 视为局部随机试验。对于那些处于阈值附近的人来说，干预可能会采取任何一种方式，有些人可能低于门槛，有些人则可能超过了门槛。在我们的示例中，在同一时间点，有些人刚刚超过 21 岁，有些人刚刚低于 21 岁。决定这一点的是某人是否在几天后出生，这是非常随机的。基于这个原因，RDD 提供了一个非常引人注目的因果故事。它不是 RCT 的黄金标准，但很接近。\n",
    "\n",
    "现在，要估计阈值处的干预效果，我们需要做的就是估计上面公式中的两个极限值并进行比较。最简单的方法是运行线性回归\n",
    "\n",
    "![img](./data/img/rdd/ols.png)\n",
    "\n",
    "为了使其工作，我们将一个高于阈值的虚拟变量与运行变量进行交叉\n",
    "\n",
    "$\n",
    "y_i = \\beta_0 + \\beta_1 r_i + \\beta_2 \\mathcal{1}\\{r_i>c\\} + \\beta_3 \\mathcal{1}\\{r_i>c\\} r_i\n",
    "$\n",
    "\n",
    "本质上，这与在阈值之上拟合线性回归并在阈值之下拟合另一个线性回归相同。参数 \\\\(\\beta_0\\\\) 是低于阈值的回归的截距，而 \\\\(\\beta_0+\\beta_2\\\\) 是高于阈值的回归的截距。\n",
    "\n",
    "这就是将运行变量在阈值处取零的技巧发挥作用的地方。在这个预处理步骤之后，阈值变为零。这导致截距 \\\\(\\beta_0\\\\) 成为阈值处的预测值，用于低于它的回归。换句话说，\\\\(\\beta_0=\\lim_{r \\to c^-} E[Y_{ti}|R_i=r]\\\\)。同理，\\\\(\\beta_0+\\beta_2\\\\) 是上述结果的极限。威奇的意思是\n",
    "\n",
    "$\n",
    "\\lim_{r \\to c^+} E[Y_{ti}|R_i=r] - \\lim_{r \\to c^-} E[Y_{ti}|R_i=r]=\\beta_2=E[ATE |R=c]\n",
    "$\n",
    "\n",
    "下面的代码展示了当我们想估计在21 岁时饮酒对死亡造成的影响。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "          <td></td>             <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th>         <td>   93.6184</td> <td>    0.932</td> <td>  100.399</td> <td> 0.000</td> <td>   91.739</td> <td>   95.498</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>agecell</th>           <td>    0.8270</td> <td>    0.819</td> <td>    1.010</td> <td> 0.318</td> <td>   -0.823</td> <td>    2.477</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>threshold</th>         <td>    7.6627</td> <td>    1.319</td> <td>    5.811</td> <td> 0.000</td> <td>    5.005</td> <td>   10.320</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>agecell:threshold</th> <td>   -3.6034</td> <td>    1.158</td> <td>   -3.111</td> <td> 0.003</td> <td>   -5.937</td> <td>   -1.269</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.table.SimpleTable'>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rdd_df = drinking.assign(threshold=(drinking[\"agecell\"] > 0).astype(int))\n",
    "\n",
    "model = smf.wls(\"all~agecell*threshold\", rdd_df).fit()\n",
    "\n",
    "model.summary().tables[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这个模型告诉我们，随着饮酒，死亡率会增加 7.6627 个百分点。 另一种说法是，酒精会使各种原因的死亡几率增加 8% ((7.6627+93.6184)/93.6184)。 请注意，这也为我们的因果效应估计提供了标准误差。 在这种情况下，效果具有统计显着性，因为 p 值低于 0.01。\n",
    "\n",
    "如果我们想直观地验证这个模型，我们可以在我们拥有的数据上显示预测值。 您可以看到，就好像我们有 2 个回归模型：一个用于高于阈值的模型，一个用于低于阈值的模型。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = drinking.plot.scatter(x=\"agecell\", y=\"all\", color=\"C0\")\n",
    "drinking.assign(predictions=model.fittedvalues).plot(x=\"agecell\", y=\"predictions\", ax=ax, color=\"C1\")\n",
    "plt.title(\"Regression Discontinuity\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果我们对其他原因做同样的事，这是我们会得到的结果。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "\n",
    "for p, cause in enumerate([\"all\", \"mva\", \"suicide\"], 1):\n",
    "    ax = plt.subplot(3,1,p)\n",
    "    drinking.plot.scatter(x=\"agecell\", y=cause, ax=ax)\n",
    "    m = smf.wls(f\"{cause}~agecell*threshold\", rdd_df).fit()\n",
    "    ate_pct = 100*((m.params[\"threshold\"] + m.params[\"Intercept\"])/m.params[\"Intercept\"] - 1)\n",
    "    drinking.assign(predictions=m.fittedvalues).plot(x=\"agecell\", y=\"predictions\", ax=ax, color=\"C1\")\n",
    "    plt.title(f\"Impact of Alcohol on Death: {np.round(ate_pct, 2)}%\")\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "RDD 告诉我们，酒精会使自杀和车祸死亡的几率增加 15%，这是一个相当大的数字。如果我们想尽量减少死亡率，这些结果是不降低饮酒年龄的有力论据。\n",
    "\n",
    "### 内核加权\n",
    "\n",
    "回归不连续性在很大程度上依赖于线性回归的外推特性。由于我们正在查看 2 条回归线的开头和结尾处的值，因此我们最好正确设置这些限制。可能发生的情况是，回归可能过于关注拟合其他数据点，而代价是在阈值处拟合不佳。如果发生这种情况，我们可能会得到错误的治疗效果衡量标准。\n",
    "\n",
    "解决此问题的一种方法是为更接近阈值的点赋予更高的权重。有很多方法可以做到这一点，但一种流行的方法是使用 **triangular kernel** 重新加权样本\n",
    "\n",
    "$\n",
    "K(R, c, h) = \\mathcal{1}\\{|R-c| \\leq h\\} * \\bigg(1-\\frac{|R-c|}{h}\\bigg)\n",
    "$\n",
    "\n",
    "这个内核的第一部分是我们是否接近阈值的指示函数。多近？这由带宽参数 \\\\(h\\\\) 确定。这个内核的第二部分是一个加权函数。随着我们远离阈值，权重变得越来越小。这些权重除以带宽。如果带宽很大，则权重会以较慢的速度变小。如果带宽很小，权重很快就会变为零。\n",
    "\n",
    "为了更容易理解，下面是这个内核应用于我们的问题的权重。我在这里将带宽设置为 1，这意味着我们只会考虑来自不超过 22 岁且不低于 20 岁的人的数据。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def kernel(R, c, h):\n",
    "    indicator = (np.abs(R-c) <= h).astype(float)\n",
    "    return indicator * (1 - np.abs(R-c)/h)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(drinking[\"agecell\"], kernel(drinking[\"agecell\"], c=0, h=1))\n",
    "plt.xlabel(\"agecell\")\n",
    "plt.ylabel(\"Weight\")\n",
    "plt.title(\"Kernel Weight by Age\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果我们将这些权重应用于我们最初的问题，酒精的影响会变得更大，至少对于死于\"所有原因\"的情况是如此。 它从 7.6627 跃升至 9.7004。 结果仍然非常显著。 另外，请注意我使用的是 `wls` 而不是 `ols`。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "          <td></td>             <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th>         <td>   93.2002</td> <td>    0.731</td> <td>  127.429</td> <td> 0.000</td> <td>   91.726</td> <td>   94.674</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>agecell</th>           <td>    0.4109</td> <td>    1.789</td> <td>    0.230</td> <td> 0.819</td> <td>   -3.196</td> <td>    4.017</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>threshold</th>         <td>    9.7004</td> <td>    1.034</td> <td>    9.378</td> <td> 0.000</td> <td>    7.616</td> <td>   11.785</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>agecell:threshold</th> <td>   -7.1759</td> <td>    2.531</td> <td>   -2.835</td> <td> 0.007</td> <td>  -12.276</td> <td>   -2.075</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.table.SimpleTable'>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = smf.wls(\"all~agecell*threshold\", rdd_df,\n",
    "                weights=kernel(drinking[\"agecell\"], c=0, h=1)).fit()\n",
    "\n",
    "model.summary().tables[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = drinking.plot.scatter(x=\"agecell\", y=\"all\", color=\"C0\")\n",
    "drinking.assign(predictions=model.fittedvalues).plot(x=\"agecell\", y=\"predictions\", ax=ax, color=\"C1\")\n",
    "plt.title(\"Regression Discontinuity (Local Regression)\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And here is what it looks like for the other causes of death. Notice how the regression on the right is more negatively sloped since it disconsiders the right most points。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "weights = kernel(drinking[\"agecell\"], c=0, h=1)\n",
    "\n",
    "for p, cause in enumerate([\"all\", \"mva\", \"suicide\"], 1):\n",
    "    ax = plt.subplot(3,1,p)\n",
    "    drinking.plot.scatter(x=\"agecell\", y=cause, ax=ax)\n",
    "    m = smf.wls(f\"{cause}~agecell*threshold\", rdd_df, weights=weights).fit()\n",
    "    ate_pct = 100*((m.params[\"threshold\"] + m.params[\"Intercept\"])/m.params[\"Intercept\"] - 1)\n",
    "    drinking.assign(predictions=m.fittedvalues).plot(x=\"agecell\", y=\"predictions\", ax=ax, color=\"C1\")\n",
    "    plt.title(f\"Impact of Alcohol on Death: {np.round(ate_pct, 2)}%\")\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "除了自杀之外，似乎使用核函数加权会使对酒精的负面影响更大。再同样的，如果我们想将死亡率降到最低，我们不应该建议降低法定饮酒年龄，因为酒精对死亡率有明显的影响。\n",
    "\n",
    "这个简单的案例涵盖了当断点回归完美运行​​时会发生什么。接下来，我们将看到一些我们应该运行的诊断步骤，以检查我们对 RDD 的信任程度，并讨论一个我们非常关心的话题：教育对收入的影响。\n",
    "\n",
    "## 羊皮效应和模糊 RDD（Fuzzy RDD）\n",
    "\n",
    "关于教育对收入的影响，经济学有两种主要观点。第一个是广为人知的论点，即教育增加了人力资本，提高了生产力，从而提高了收入。从这个观点来看，教育实际上会让你变得更好。另一种观点认为，教育只是一种信号机制。它只是让您完成所有这些艰巨的测试和学术任务。如果你能做到，它就向市场表明你是一名优秀的员工。这样，教育不会让你更有效率。它只会告诉市场你一直以来的生产力。这里重要的是文凭。如果你有它，你会得到更多的报酬。我们将此称为**羊皮效应**，因为过去文凭是用羊皮印刷的。\n",
    "\n",
    "为了检验这一假设，[Clark and Martorell](https://faculty.smu.edu/millimet/classes/eco7321/papers/clark%20martorell%202014.pdf) 使用断点回归来衡量 12 年级毕业对收入的影响。为了做到这一点，他们必须考虑一些运行变量，使高于它的学生毕业，而低于它的学生则不毕业。他们在德克萨斯州的教育系统中发现了这样的数据。\n",
    "\n",
    "为了在德克萨斯州毕业，必须通过考试。考试从 10 年级开始，学生可以做多次，但最终，他们将在 12 年级末面临最后一次考试机会。这个想法是从参加最后一次考试机会的学生那里获取数据，并将那些几乎没有通过考试的学生与那些勉强通过考试的学生进行比较。这些学生将拥有非常相似的人力资本，但不同的资质水平。也就是说，那些勉强通过的人也将获得文凭。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>avgearnings</th>\n",
       "      <th>minscore</th>\n",
       "      <th>receivehsd</th>\n",
       "      <th>n</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11845.086</td>\n",
       "      <td>-30.0</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9205.679</td>\n",
       "      <td>-29.0</td>\n",
       "      <td>0.387097</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8407.745</td>\n",
       "      <td>-28.0</td>\n",
       "      <td>0.318182</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11114.087</td>\n",
       "      <td>-27.0</td>\n",
       "      <td>0.377778</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10814.624</td>\n",
       "      <td>-26.0</td>\n",
       "      <td>0.306667</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   avgearnings  minscore  receivehsd   n\n",
       "0    11845.086     -30.0    0.416667  12\n",
       "1     9205.679     -29.0    0.387097  31\n",
       "2     8407.745     -28.0    0.318182  44\n",
       "3    11114.087     -27.0    0.377778  45\n",
       "4    10814.624     -26.0    0.306667  75"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sheepskin = pd.read_csv(\"./data/sheepskin.csv\")[[\"avgearnings\", \"minscore\", \"receivehsd\", \"n\"]]\n",
    "sheepskin.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "再次，此数据按运行变量分组。 它不仅包含运行变量（minscore，已经以零为中心）和结果（avgearnings），而且还包含在该分数单元中接收文凭的概率和调用的大小 (n)。 因此，例如，在分数低于阈值 -30 的单元格中的 12 名学生中，只有 5 人能够获得文凭 (12 * 0.416)。\n",
    "\n",
    "这意味着干预分配中存在一些滑移。 一些低于及格门槛的学生无论如何都设法获得了文凭。 在这里，回归的断点是**模糊的**，而不是干脆清晰的。 请注意获得文凭的概率不会在阈值处从零跳到一。 但它确实从 50% 跃升至 90%。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sheepskin.plot.scatter(x=\"minscore\", y=\"receivehsd\", figsize=(10,5))\n",
    "plt.xlabel(\"Test Scores Relative to Cut off\")\n",
    "plt.ylabel(\"Fraction Receiving Diplomas\")\n",
    "plt.title(\"Last-chance Exams\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们可以将模糊 RD 视为一种不合规性。通过门槛应该让每个人都能获得文凭，但是那些“从不接受”的学生，却没有得到它。同样，低于门槛应该会阻止你获得文凭，但是那些“总是接受“的学生，无论如何都设法获得它。\n",
    "\n",
    "就像当我们有潜在的结果时，我们在这种情况下也有潜在的干预状态。 \\\\(T_1\\\\) 是每个人在超过阈值时都会得到的待遇。 \\\\(T_0\\\\) 是每个人在低于阈值时都会得到的待遇。您可能已经注意到，我们可以将**阈值视为工具变量**。就像在 IV 中一样，如果我们直接地估计干预效果，它将偏向零值。\n",
    "\n",
    "![img](./data/img/rdd/rdd_fuzzy.png)\n",
    "\n",
    "干预的概率小于 1，甚至高于阈值，使得我们观察到的结果小于真正的潜在结果 \\\\(Y_1\\\\)。出于同样的原因，我们观察到的低于阈值的结果高于真正的潜在结果 \\\\(Y_0\\\\)。这使得阈值处的干预效果看起来比实际要小，我们将不得不使用 IV 技术来纠正它。\n",
    "\n",
    "就像我们假设潜在结果的平稳性一样，我们现在假设它用于潜在的治疗。此外，我们需要假设单调性，就像在 IV 中一样。万一你不记得了，它说明了 \\\\(T_{i1}>T_{i0} \\ \\forall i\\\\)。这意味着从左到右越过门槛只会增加您获得文凭的机会（或者没有拒绝者）。有了这两个假设，我们就有了 LATE 的 Wald Estimator。\n",
    "\n",
    "$$\n",
    "\\dfrac{\\lim_{r \\to c^+} E[Y_i|R_i=r] - \\lim_{r \\to c^-} E[Y_i|R_i=r]}{\\lim_{r \\to c^ +} E[T_i|R_i=r] - \\lim_{r \\to c^-} E[T_i|R_i=r]} = E[Y_{1i} - Y_{0i} | T_{1i} > T_{0i}, R_i=c]\n",
    "$$\n",
    "\n",
    "请注意，这是在两种意义上的局部估计。首先，它之所以是局部的，因为它只给出阈值 \\\\(c\\\\) 处的处理效果。这是 RD 位置。其次，它之所以是局部的第二个原因，在于它只估计服从者的处理效果。这是 IV 位置。\n",
    "\n",
    "为了估计这一点，我们将使用 2 线性回归。可以像我们之前所做的那样估计分子。为了得到分母，我们只需将结果替换为处理。但首先，让我们谈谈我们需要运行的健全性检查，以确保我们可以信任我们的 RDD 估计。\n",
    "\n",
    "### 麦克雷测试（McCrary Test）\n",
    "\n",
    "可能打破我们 RDD 论点的一件事是，人们是否可以操纵他们站在门槛的位置。在羊皮示例中，如果刚好低于阈值的学生找到一种绕过系统的方法来稍微提高他们的考试成绩，就会发生这种情况。另一个例子是当您需要低于某个收入水平才能获得政府福利时。一些家庭可能会故意降低收入，只是为了有资格参加该计划。\n",
    "\n",
    "在这种情况下，我们往往会看到一种现象，即运行变量密度上的聚束现象（bunching）。这意味着我们将有很多实体略高于或略低于阈值。为了检查这一点，我们可以绘制运行变量的密度函数并查看阈值周围是否有任何尖峰。对于我们的例子，密度由我们数据中的“n”列给出。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JiIgo51E8JmjcuHHw9vZGpUqV0LFjR3mF5/DwcGzbtg3Pnz/HwoULFe94586daq9XrlwJR0dHBAcHo0mTJpAkCcuXL8eQIUPg5eUFAFi+fDmcnZ0RGBiI7t27IywsDEePHsXBgwfh7u4OAFiwYAGaNGmC8PBwODs7Y8eOHXj9+jWWL18OExMTlCxZErdu3cKyZcswYMAAPt5PREQ50vv375GQkKC2zdjYGM+fP1f0/uwQa2Zm9lULuCt+Z40aNfD7779jwoQJWLJkiVpbuXLlsG7dOlSvXv2LE4mPj0dycjJUKhUA4N69e4iOjoanp6ccY2JigmrVqiEkJATdu3dHaGgo8ubNiypVqsgxVatWhZmZGUJCQuDs7IzQ0FB4eHjAxMREjqlXrx5mzpyJe/fuoUiRIl+cMxERUVb0/v17vHz5EiqVSu2P/Tx58sDY2FhRH1k9VpIkiKIIc3PzLy6EvmjG6OjoaHmBVQcHB9jY2HzRzj/WrVs33L59GydOnIC+vj5CQkLQqFEjXL16VW1RVj8/P0RFRWHnzp2YN28eNm7ciL///lutr3LlyqFr164YNmwYvL29YWdnh6VLl8rtDx48QJkyZXD48GH5CtKnvuRROyIioqzAyMgI1tbWOf5uhyRJePLkCd6+fZuqzdnZ+bPv/6LSycbGRiuFT4px48YhODgYBw8ehL6+vtb6/RofH7yUW2tKMFZ3sZm9f8Zmjf0zVnmsan1kqm1id/tvtn/GZt7+nz9/rnYHJEViYqLiqzDZJValUiF//vwaHbMUGhVBSUlJOHbsGCIiIiCKYqonrARBwKhRozRKYOzYsdi5cyf27t2rdmsqpciKiYlRuxIUExMDa2trAIC1tTViY2MhSZJc7UqShKdPn6rFxMTEqO0z5XVKDBEREeU+iougS5cu4ccff8SjR4/Sfbxc0yJo9OjR2LVrF/bu3YvixYurtTk5OcHGxgZBQUGoUKECgA8V4fnz5zFt2jQAgLu7O+Lj4xEaGiqPCwoNDUVCQoL82t3dHVOmTFGrJoOCglCoUCE4OTkpzpWIiIhyFsWPyA8fPhyJiYnYvHkz7t69i2fPnqX6iouLU7zjESNGYMuWLVi9ejVUKhWio6MRHR2N+Ph4AB8Kqn79+mHRokXYs2cPrl+/jv79+8PMzAxt27YFALi4uKB+/foYOnQoQkNDERoaiqFDh6JRo0byJbG2bdvCxMQE/fv3x/Xr17Fnzx4sXLgQ/fv3z/H3SomIiCh9iq8EXbt2DRMmTECTJk20suM1a9YAgPz4e4rRo0dj7NixAIDBgwfj9evXGDlyJERRRMWKFbFz506Ym5ur9TNq1Ci0adMGANCkSRPMnj1bbs+fPz927dqFESNGoG7dulCpVPDz88OAAQO08jmIiIiyg7TGiOnS58afZQWKiyA7Ozut7jitSRc/JQgCxo4dKxdFaVGpVFi1alWG/ZQqVQoHDhzQNEUiIiLKwRQXQUOHDsXixYvRtWtX5MuXT5c5ERHRN/bfVQJT4MyHf2eHv+QpZ2nWrBlcXV2RP39+/PrrrxAEAR06dMC0adOgp6d4BI9i6RZBixYtSrXN1NQUFSpUgJeXF+zt7VM9zi4IAgYNGqT1JImIcjL12xQfipD0ChBNYomyox07dsDX1xeHDx/GxYsX0b9/f7i5ucnjgbUp3SJoypQp6b5p3bp1aW5nEURERERfw8XFBePHjwcAFC5cGFu3bsXJkye/bRH06SzMRERERLpWqlQptde2trap5vvTlnSLIEdHR53skIiIiCg9hoaGaq8FQUh3fsKvpXhg9Js3b/Dq1SsUKFBA3hYbG4sNGzbg+fPn8PLykic1JCIiIsrqFBdBgwYNws2bN3Hy5EkAwKtXr1C/fn1EREQAAJYtW4a9e/eiatWqOkmUiIgyX1oDs4G0nyTTJJYoMygugs6dO4dOnTrJrwMDAxEREYHAwECUKVMGrVu3xty5cxEYGKiTRImIiOjLid3ts8SiqFmJ4iIoJiYG9vb/Ve/79++Hu7s76tWrBwDo1KkTFixYoP0MiYiIKFf4888/U21bvny5zvaneOahvHnzyrM8v3//HufOnUOdOnXkdhMTE7x8+VLb+RERERHphOIrQeXLl8dvv/2GWrVq4cCBA4iPj0fjxo3l9rt378La2lonSRIRERFpm+IiaMKECfD29kbdunUhSRJatWqF8uXLy+379u1DlSpVdJIkERERkbYpLoLKlSuHCxcuICQkBPny5UONGjXkNlEU0atXL1SvXl0nSRIRERFpm+IiCAAsLCzQtGnTVNtVKhX69euntaSIiIiIdE2jJVnfvn2LjRs3onfv3mjVqpW8tIYoiti6dSsiIyM/0wMRERF9C7qaZTkr+drPqPhKUFxcHFq0aIHr16/D2toaMTEx8tNi+fLlw8yZM3Hz5k1MnTr1qxIiIiKir2NmZgZRFKFSqSAIQmanoxOSJEEURZibm39xH4qLoMmTJ+PBgwc4ePAgihUrhmLFisltenp6aNmyJY4cOcIiiIiIKJMZGBjA3NwcL168UNv+4sUL5MuXT1Ef2SHW3NwcBgYajexRo/idBw8ehK+vL6pUqYK4uLhU7d9//z02bdr0xYkQERGR9hgYGCB//vxq2548eQIHBwdF789usV9C8Zigly9fonDhwum2v3nzBklJSVpJioiIiEjXFF8J+u6773Dp0iV07do1zfbjx4+jRIkSWkuMiCg7S2vxUC4cSpS1KL4S1LVrV2zZsgUBAQFITk4GAAiCgFevXmHKlCk4fvw4unfvrrNEiYiIiLRJ8ZUgX19f3Lx5E76+vvJI7B49ekAURSQlJaFXr15qq8wTERERZWUaDalesGAB2rdvj127duHOnTtITk5G0aJF4e3tjWrVqukqRyIiIiKtU1QEvX79GiNGjEDDhg3h5eXFNcKIiIgo21M0JsjExAR//PEHnj9/rut8iIiIiL4JxbfDypcvj6tXr+oyFyKiLC2tJ74A8KkvomxK8dNh/v7+2LNnD1avXo23b9/qMiciIiIinVN8JahXr14AgNGjR2P8+PGwtbWFiYmJWowgCAgODtZuhkRElOPxKhtlBsVFkKWlJaysrODs7KzLfIiIiIi+CcVF0J9//qnLPIiIiIi+KcVjgoiIiIhyEo3Xn7958yYiIiIgiiIkSUrV3qFDB60kRkRERKRLiougu3fvok+fPrh48WKaxQ/wYWA0iyAiIiLKDhQXQUOGDMH169fh7+8PDw8PqFQqHaZFREREpFuKi6CQkBAMGzYMvr6+usyHiIiI6JtQPDDawsIC+fLl02UuRERERN+M4iKoR48eCAgIQFJSki7zISIiIvom0r0dtmvXLrXXRYsWxfv371G9enV06NAB9vb20NfXT/U+b29v7WdJREREpGXpFkE9evSAIAjyk2Af/3vKlClpvkcQBBZBRESkU1xig7Ql3SJo79693zIPIiIiom8q3SKoRo0aOHv2LFxcXGBpaamTnZ89exZLlizB33//jaioKCxduhSdOnWS2/v164etW7eqvadSpUo4evSo/PrNmzeYMGECfv/9dyQmJqJWrVqYN28e7O3/+4vgwYMHGDFiBE6fPg1jY2O0bdsWM2bMgJGRkU4+FxEREWV9GQ6MbtGiBYKCgnS284SEBJQsWRI///xzqhXpU9SpUwdhYWHy144dO9Tax44di71792Lt2rXYv38/Xr58CR8fH3kAd1JSEnx8fBAfH4/9+/dj7dq12LNnD8aPH6+zz0VERERZX4bzBKU3M7S2NGzYEA0bNgQA9O/fP82YPHnywMbGJs2258+f47fffsPSpUtRt25dAMDKlStRpkwZnDhxAvXq1cPx48dx48YNXL16FYULFwYATJ06FYMGDcLEiRP52D8REVEuleUXUD1//jyKFSuGihUrYtCgQYiJiZHbLl++jHfv3sHT01PeVrhwYbi4uCAkJAQAEBoaChcXF7kAAoB69erhzZs3uHz58jf7HERERJS1fHbGaEEQvkUeaapfvz5atGgBJycn3L9/HzNmzEDLli1x4sQJ5MmTB0+ePIG+vj4sLCzU3mdlZYUnT54AAJ48eQIrKyu1dgsLC+jr68sxaQkPD8/wdUYYq7vYzN4/Y7PG/rUZW/mM6Uev/nvS6EKNV2lEm6axLb3+U8emn0d2iv26Y/DtYzWP0WVsZu8/N8U6Ozt/Nv6zRdCkSZMwZ84cRTsXBAHBwcGKYpVo06aN/O9SpUrBzc0NZcqUwaFDh9CyZUut7SctHx+88PBwRQeTsbqNzez9MzZr7F/rsWci09yc5nu+MjbdPLJT7Dc8XlqJ/Uhmfz9m9v4Zm9pniyBzc/NUV1IyS6FChWBnZ4c7d+4AAKytrZGUlITY2Fi1J9hiYmLg4eEhx6TcGksRGxuLpKQkWFtbf7vkiYiIKEv5bBE0YsQItGvX7lvk8lmxsbGIioqSB0q7ubnB0NAQQUFBco6RkZEICwtDlSpVAADu7u6YO3cuIiMj5cfmg4KCkCdPHri5uWXK5yAiIqLMp3gVeV2Ij4+Xr+okJyfj4cOHuHLlCgoUKIACBQrg559/RsuWLWFjY4P79+9j2rRpsLKyQvPmzQEA+fPnx48//ojJkyfDysoKBQoUwPjx41GqVCnUqVMHAODp6YkSJUqgb9++mDFjBp49e4ZJkyahS5cufDKMiIgoF8vUIujSpUto0aKF/Nrf3x/+/v7o0KED5s+fj+vXr2Pbtm14/vw5bGxsULNmTaxfvx7m5uZq79HX10f37t3lyRJXrFghr2umr6+P7du3Y8SIEWjcuDGMjY3Rrl07TJ8+/Zt/XiIiIso6MrUIqlmzJkRRTLd9586dn+0jT548mDNnToaDtx0cHLB9+/YvSZGIiIhyqAyLoL///ltnS2YQERERZaYMiyBHR8dvlQcREZHWccV5ykiWnzGaiIiISBdYBBEREVGuxCKIiIiIciUWQURERJQrafyI/IkTJ3D69GnExMRgwIABKF68OOLj4/H333+jVKlSUKlUOkiTiIiISLsUF0GvX79G586dERQUJG9r06YNihcvDiMjI3Tt2hW9e/fG6NGjdZIoEZFSfCKIiJRQfDts+vTpOHPmDFatWoWrV69CkiS5zcjICK1atcLBgwd1kiQRERGRtikugv744w/06tULbdu2hYmJSap2Z2dnREREaDM3IiIiIp1RXATFxsbCxcUl3XZBEJCYmKiVpIiIiIh0TXERVLhwYYSFhaXbHhwcjO+++04rSRERERHpmuIiqF27dtiwYQPOnz8vbxMEAQCwdu1a/PHHH+jQoYP2MyQiIiLSAcVPhw0bNgwXL15E8+bNUaxYMQiCgDFjxiAuLg7R0dFo3Lgx+vfvr8tciYiIiLRGcRFkZGSEHTt2YMeOHfjjjz8gCALev3+PcuXKwdvbGz4+PvKVISIiIqKsTuPJEtu1a4d27drpIhciIiKib4bLZhAREVGupNGVoGPHjuG3335DREQERFFUmzAR+DBQ+vLly9rMj4iI6JtIa6ZxzjKesykughYvXowpU6bA2toaFSpUQMmSJXWZFxEREZFOKS6CVqxYgVq1amHHjh0wNDTUZU5EREREOqd4TJAoivDy8mIBRERERDmC4itBFStWRHh4uC5zISJKF1eGJyJtU3wlaO7cudi3bx8CAgJ0mQ8RERHRN5HulaAqVaqk2vb27Vv07dsXQ4cORaFChaCvr6/WLggCgoODtZ8lERERkZalWwRZWlqmmgHaysoKxYoV03lSRERERLqWbhH0559/fss8iIiIiL4pxWOCtm7dinv37qXbfv/+fWzdulUrSRERERHpmuIiyM/PD6Ghoem2//XXX/Dz89NKUkRERES6prgI+nSJjE+9fv061UBpIiIioqwqw3mCHjx4gPv378uvb926hbNnz6aKE0UR69evh5OTk/YzJCIiItKBDIugzZs3Y9asWRAEAYIgYN68eZg3b16qOEmSoK+vj8WLF+ssUSIiIiJtyrAI8vb2RokSJQAA3bp1g6+vLzw8PNRiBEGAmZkZypYtCysrK91lSkRERKRFGRZBLi4ucHFxAQAsXboU1atX5y0vIiIiyhEUrx3WsWNHXeZBRERE9E0pfjqMiIiIKCdhEURERES5kuLbYUREuqBaH/n//zIFznz4t9jdPvMSIqJcg1eCiIiIKFfS2tph9+7d49phRESUK6jWR8pflc+YfnRFk7ITra0ddvHiRa4dRkRERNlGpq4ddvbsWbRv3x4lSpSASqXC5s2bU+3T398frq6usLW1RbNmzXDjxg21GFEU0adPHzg6OsLR0RF9+vSBKIpqMdeuXUPTpk1ha2uLEiVKYNasWZ/9PERERJSzZeraYQkJCShZsiQ6dOiAvn37pmpftGgRli5diqVLl8LZ2RmzZ8+Gt7c3Lly4AHNzcwBAr1698PDhQwQGBgIABg0aBF9fX2zfvh0A8OLFC3h7e6NatWo4fvw4wsPD4efnB1NTUwwcOFCjfImIiCjnyNS1wxo2bIiGDRsCAPr375+qz+XLl2PIkCHw8vICACxfvhzOzs4IDAxE9+7dERYWhqNHj+LgwYNwd3cHACxYsABNmjRBeHg4nJ2dsWPHDrx+/RrLly+HiYkJSpYsiVu3bmHZsmUYMGAABEHQKGciIiLKGbLs2mH37t1DdHQ0PD095W0mJiaoVq0aQkJC0L17d4SGhiJv3ryoUqWKHFO1alWYmZkhJCQEzs7OCA0NhYeHB0xMTOSYevXqYebMmbh37x6KFCmitZyJiIgo+8iya4dFR0cDQKrCysrKClFRUQCAJ0+ewMLCQu1qjiAIsLS0xJMnT+QYOzu7VH2ktKVXBIWHh2f4OiOM1V1sZu+fsbro01The1LHZbfY9I9FdorNmsdWV7HaObaaxTBWO7HOzs6fjefaYen4+OCl3FpTgrG6i83s/TNWR32eSf1ocZrvSSMuu8WmeyyyU2wWPba6itXKsf1/mf1/l7GpaTRjdGJiIvbu3YvLly/jxYsXSE5OVmsXBAG//PKLRgmkx8bGBgAQExMDBwcHeXtMTAysra0BANbW1oiNjYUkSfLVIEmS8PTpU7WYmJgYtb5TXqfEEBERUe6juAh6+PAhWrRogYiICOTPnx8vXrxAgQIFIIoikpOTYWFhATMzM60l5uTkBBsbGwQFBaFChQoAPhRh58+fx7Rp0wAA7u7uiI+PR2hoqDwuKDQ0FAkJCfJrd3d3TJkyBYmJiTA2NgYABAUFoVChQt/s1h5RbsOlMIgoO1A8T9DkyZMRFxeHw4cP4+LFi5AkCevWrcOjR48wceJEmJiYYPfu3RrtPD4+HleuXMGVK1eQnJyMhw8f4sqVK3jw4AEEQUC/fv2waNEi7NmzB9evX0f//v1hZmaGtm3bAvgwZql+/foYOnQoQkNDERoaiqFDh6JRo0byJbG2bdvCxMQE/fv3x/Xr17Fnzx4sXLgQ/fv355NhREREuZjiIujEiRPo2bMnKleuDD29/96WJ08eDBs2DNWqVcPYsWM12vmlS5dQq1Yt1KpVC69fv4a/vz9q1aqFn376CQAwePBg9OvXDyNHjkTdunXx+PFj7Ny5U54jCADWrFmD0qVLo02bNmjTpg1Kly6NlStXyu358+fHrl27EBUVhbp162LkyJHw8/PDgAEDNMqViIiIchbFt8MSEhLkJ6mMjIwAAC9fvpTbPTw8MGnSJI12XrNmzVSzO39MEASMHTs2w+JKpVJh1apVGe6nVKlSOHDggEa5ERERUc6m+EpQoUKF8PjxYwCAmZkZChQogKtXr8rtDx48gKGhofYzJCIiItIBxVeCUpadGDVqFACgZcuW+OWXX2BgYIDk5GSsWLECjRo10lmiRERERNqkuAjq378/goKC5KespkyZgoiICHn8To0aNfDzzz/rLFEiylx84ovoy/D/TtaluAgqVaoUSpUqJb9WqVT4448/IIoi9PX11QYrExEREWV1Gk2WmBaVSqWFNIiIiIi+LcUDo4mIiIhyEhZBRERElCuxCCIiIqJciUUQERER5UosgoiIiChXUlwEPXnyBH///bfatlu3bmHIkCHo3r079u7dq/XkiIiIiHRF8SPyI0aMQExMjLwG17Nnz9C0aVM8f/5cXkF+y5YtaNy4sc6SJSIiItIWxVeCLly4gPr168uvt2/fDlEUcfLkSdy+fRtVqlTB4sWLdZIkERERkbYpLoLi4uJgY2Mjvz548CCqVauGkiVLwtDQEG3atMHNmzd1kiQRERGRtim+HVagQAFER0cDAF69eoWQkBCMHj1abhcEAW/evNF+hkSkM/+taQSkrGvENY2IKLdQXARVrVoVa9euRfHixXHs2DG8efMGTZo0kdvDw8NRqFAhnSRJREREpG2Ki6DJkyfD29sbXbp0AQAMGDAALi4uAICkpCTs2bMHDRo00E2WRERERFqmuAgqWrQo/vrrL9y8eRPm5uZwcnKS2169eoU5c+agdOnSOkmSiIiISNs0WkXewMAgzULH3NwczZo101pSRERERLqm+Omw8+fPY/Xq1Wrbfv/9d1SqVAnOzs4YM2YMkpOTtZ4gERERkS4oLoJmzpyJc+fOya///fdf9OvXD3p6enBzc8OqVauwYsUKnSRJREREpG2Ki6CbN2+iYsWK8utt27bB2NgYR48exY4dO+Dj44NNmzbpJEkiIiIibVNcBL18+RIqlUp+fezYMdStWxf58uUDAHh4eOD+/ftaT5CIiIhIFxQPjLa1tUVYWBgAICoqCleuXEG3bt3k9hcvXsDAQKNx1kRERPSR/yYw/TB5KQBOYKpDiquWFi1aYPXq1Xjz5g0uXrwIY2NjNG3aVG7/559/1B6bJyIiIsrKFBdBY8eOxZMnTxAQEIB8+fJh2bJlsLKyAvDhKtDevXvRu3dvnSVKREREpE2KiyAzMzOsWrUqzba8efPi+vXrMDU11VpiRPRluB4YEZEyigdGfywxMRGPHj3C27dvP3Sip4f8+fPD0NBQq8kRERER6YpGRdDZs2fRuHFjFC5cGKVLl8b58+cBALGxsWjZsiWOHz+ukySJiIiItE1xEXT69Gm0atUKz58/R+/evSFJktxmYWEBANi4caP2MyQiIiLSAcVF0E8//YSyZcvi9OnTGDFiRKr26tWr43//+59WkyMiIiLSFcVF0OXLl+Hj4wMDAwMIgpCqvVChQnjy5IlWkyMiIiLSFcVFkKGhId69e5due2RkJMzNzbWSFBEREZGuKS6CqlSpgt27d6fZFh8fj82bN6NGjRpaS4yIiIhIlxQXQWPHjsWVK1fQunVrHDhwAABw5coVrFu3DrVr18azZ88wcuRInSVKREREpE2KJ0usUKECAgMDMWzYMAwYMAAAMGnSJADAd999hx07dqBkyZK6yZIol0trAkSAawoREX0NjVY8rVGjBkJDQ3H16lXcvn0bycnJKFq0KNzc3NIcLE1ERESUVX3Rsu9lypRBmTJltJ0LERERKcQV57+exkXQzZs3ERERAVEU1SZMTNGhQwetJEZERESkS4qLoLt376JPnz64ePFimsUPAAiCoNUiyN/fH7NmzVLbZm1tjVu3bgEAJEnCzz//jA0bNkAURVSsWBFz585FiRIl5HhRFDFq1CgcPHgQANC4cWPMnj0bKpVKa3kSERFR9qO4CBoyZAiuX78Of39/eHh4fLMiwtnZGfv27ZNf6+vry/9etGgRli5diqVLl8LZ2RmzZ8+Gt7c3Lly4IM9Z1KtXLzx8+BCBgYEAgEGDBsHX1xfbt2//JvkTERFR1qS4CAoJCcGwYcPg6+ury3xSMTAwgI2NTartkiRh+fLlGDJkCLy8vAAAy5cvh7OzMwIDA9G9e3eEhYXh6NGjOHjwINzd3QEACxYsQJMmTRAeHg5nZ+dv+lmIiIgo61A8T5CFhQXy5cuny1zSFBERAVdXV5QtWxY9evRAREQEAODevXuIjo6Gp6enHGtiYoJq1aohJCQEABAaGoq8efOiSpUqckzVqlVhZmYmxxAREVHupPhKUI8ePRAQEIDevXur3ZLSpUqVKmHZsmVwdnbG06dPMWfOHDRs2BDBwcGIjo4GAFhZWam9x8rKClFRUQCAJ0+ewMLCQu3xfUEQYGlp+dl1zsLDwzN8rcl7Gau92Mzef+bFmmrwntSx6fednWK/7hhkhdise2w1ic2ax1ZXsVn3PGgaq1lMTohVcrdHcRFUpEgRvH//HtWrV0eHDh1gb2+fZjHk7e2ttMvPatCggdrrSpUqwc3NDVu2bEHlypW1tp+0fHzwNLl1xljdxWb2/rUdqz4B4n/SfMT1TNqxafafRmy6eWSn2K88BlkhNsseW01is+ix1VVslj0Pmsb+v+zws/FbxKZQXAT16tVL/veUKVPSjBEEQatF0Kfy5s0LV1dX3LlzB82bNwcAxMTEwMHBQY6JiYmBtbU1gA9PksXGxkKSJPlqkCRJePr0qRxDREREuZPiImjv3r26zEORxMREhIeHo2bNmnBycoKNjQ2CgoJQoUIFuf38+fOYNm0aAMDd3R3x8fEIDQ2VxwWFhoYiISFBbZwQERFRTsVld9KnuAjKjBXiJ0yYgMaNG6Nw4cLymKBXr16hQ4cOEAQB/fr1w/z58+Hs7IxixYph7ty5MDMzQ9u2bQEALi4uqF+/PoYOHYqFCxcCAIYOHYpGjRrxyTAiIqJc7ouWzfhWHj16hF69eiE2NhaWlpaoVKkSjhw5AkdHRwDA4MGD8fr1a4wcOVKeLHHnzp3yHEEAsGbNGowaNQpt2rQBADRp0gSzZ8/OlM9DOR//4iIiyj40KoKOHTuG3377Ld1lMwRBwOXLl7WW3Lp16zJsFwQBY8eOxdixY9ONUalUWLVqldZyIiIiopxBcRG0ePFiTJkyBdbW1qhQoQJKliypy7yIiIiIdEpxEbRixQrUqlULO3bsgKGhoS5zIiIiItI5xTNGi6IILy8vFkBERESUIygugipWrKjRrI1EREREWZniImju3LnYt28fAgICdJkPERER0TeR7pigtCYTfPv2Lfr27YuhQ4eiUKFCqZbNEAQBwcHB2s+SKBPxsXciopwp3SLI0tJSbeFR4MPipMWKFdN5UkRERES6lm4R9Oeff37LPIiIiCiT5bYr34rHBG3duhX37t1Lt/3+/fvYunWrVpIiIiIi0jXFRZCfnx9CQ0PTbf/rr7/g5+enlaSIiIiIdE3xZImfLpHxqdevX6caKE2Ulf132TfnX/IlIqLUMiyCHjx4gPv378uvb926hbNnz6aKE0UR69evh5OTk/YzJCIiItKBDIugzZs3Y9asWRAEAYIgYN68eZg3b16qOEmSoK+vj8WLF+ssUSIiIiJtyrAI8vb2RokSJQAA3bp1g6+vLzw8PNRiBEGAmZkZypYtCysrK91lSkRERKRFGRZBLi4ucHFxAQAsXboU1apVQ5EiRb5FXkREREQ6pXhgdMeOHeV/P336VB4r5OjoCEtLS+1nRkRERKRDiosgADh//jzGjx+Py5cvq22vUKECZsyYgapVq2ozNyIiIiKdUVwEnT9/Hq1atULevHnh5+eH4sWLA/jwxNi2bdvg5eWF3bt3sxCiTMXH3omIvo2cMLu04iJo5syZcHR0xKFDh1CwYEG1tmHDhqFhw4aYOXMm9u7dq/UkiYiIiLRNcRF06dIljBkzJlUBBAAFChRAly5dMGvWLK0mRwTw6g4REemG4mUz9PX18fbt23Tb37x5Az09xd0RERERZSrFVUuVKlWwZs0aREREpGqLiIjAmjVrUs0hRERERJRVKb4dNnnyZDRp0gRVqlRBkyZNUKxYMQBAeHg4Dh48iDx58mDSpEk6S5SIiIhImxQXQaVLl8axY8cwbdo0HDlyBLt37wYAmJqaolGjRpgwYYL8xBgRERFRVqfRPEHFixfHpk2bkJycjKdPnwIALC0tORaIiIiIsh2NiqAUgiDIhY8gCFpNiIiIiHKWrDqnkEZF0J07dzBt2jQcO3YMCQkJAAAzMzM0aNAAEyZMwHfffaeTJCnnSes/RGb/ZyAiotxFcRF048YNNGrUCImJiWjSpInajNF//vknjh8/jgMHDsirzhMRERFlZYqLoClTpsDU1BQnTpxIdcXn7t27aNKkCaZOnYpt27ZpPUnKHnh1h4iIshPFI5rPnz+PXr16pXnLq2jRoujZsyfOnTun1eSIiIiIdEXxlaCkpCTkyZMn3XZjY2MkJSVpJSnKOnh1h4iIcirFV4LKlSuHjRs3QhTFVG2iKGLjxo1wc3PTYmpEREREuqP4StC4cePg7e2NSpUqoWPHjmozRm/btg3Pnz/HwoULdZUnERERkVYpLoJq1KiB33//HRMmTMCSJUvU2sqVK4d169ahevXqWk+QtC+rztdARET0LYdhaDRPUK1atXDq1ClER0fjwYMHAAAHBwfY2NjoJDkiIiIiXfmiGaNtbGxY+BAREVG2plERJEkSTp06hXv37kEURUiSpNYuCAIGDRqk1QRJGd7iIiIi0oziIujy5cvo3r077t27l6r4ScEiiIiIiL6Vrx0/pLgIGjx4MOLi4rBgwQJUrFgR+fLl0yRPIiIioixFcREUFhaG8ePHo2vXrrrMJ8fT5LYVb3ERERHpjuLJEr///vt0b4NlF2vWrEHZsmVhY2OD2rVrc5kPIiKiXExxETR27FisXr1afjQ+u9m5cyfGjBmD4cOH49SpU3B3d0e7du209nlU6yOhWh+JymdM5X8TERFR1qX4dljz5s2RmJgId3d31KxZE3Z2dtDX11eLEQQBc+fO1XqS2rB06VJ07NhRvp03Z84cHDt2DOvWrcPkyZMzOTsiIiL61gRRFBXd4zp16hQ6deqE+Pj49DsTBMTFxWktOW15+/YtChUqhLVr16JVq1by9hEjRuD69evYv39/5iVHREREmULxlaAxY8YgX7582LhxY7Z7Oiw2NhZJSUmwsrJS225lZYUnT55kUlZERESUmRSPCbp79y4GDRqEunXrZqsCiIiIiCgtiosgV1dXPHv2TJe56IyFhQX09fURExOjtj0mJgbW1taZlBURERFlJsVF0PTp07FhwwaEhIToMh+dMDIygpubG4KCgtS2BwUFoUqVKpmUFREREWUmxWOCFi1aBDMzMzRp0gTFihVD4cKF03w6LCAgQOtJaoOfnx98fX1RsWJFVKlSBevWrcPjx4/RvXv3zE6NiIiIMoHiIujmzZsQBAGFCxdGYmIi/v3331QxgiBoNTltat26NeLi4jBnzhxER0ejRIkSCAgIgKOjY2anRkRERJlA8SPyRERERDmJ4jFBRERERDmJ4tthnzp9+jQCAgLw+PFjFC9eHH379oWDg4M2cyMiIiLSmQxvh/38889YtGgRrl69CktLS3n75s2bMXDgQLUFVS0tLXHs2DGOsSEiIqJsIcPbYadPn4anp6daAfTmzRuMHTsW+fLlw+7du/Hw4UOsW7cO8fHxmD9/vs4TJiIiItKGDIugO3fuwM3NTW3byZMn8fLlSwwaNAi1atWCmZkZvL298cMPP+DEiRM6TJWIiIhIezIsgp49ewZbW1u1badPn4YgCGjUqJHadjc3Nzx+/Fj7GRIRERHpQIZFkI2NDaKiotS2nT9/HqampnB1dVXvSE8PRkZG2s+QiIiISAcyLIIqVqyIrVu3QhRFAMA///yDS5cuoXbt2qlmiw4LC4O9vb3OEiUiIiLSpgwfkR89ejRq166NihUrwsXFBVevXoUgCBgyZIhanCRJ2LdvHzw9PXWZKxEREZHWZHglyMXFBXv27EHFihXx9OlTVKlSBTt37kTlypXV4k6fPo28efOiZcuWOk2WiIiISFu4bAYRERHlSlw2g4iIiHIlFkFERESUK7EIIiIiolyJRRARERHlSiyCiIiIKFdiEURERES5EosgIiIiypVYBBEREVGuxCKIiIiIciUWQURERJQrsQgiIiKiXIlFEBEREeVKLIKIiIgoV2IRRERERLkSiyAiIiLKlVgEERERUa7EIoiIiIhyJRZBRERElCuxCCIiIqJciUUQERER5UosgoiIiChXYhFEREREuRKLICIiIsqVWAQRERFRrsQiiIiIiHIlFkFERESUK7EIUiA8PJyxWSA2s/fP2Kyxf8ZqHpvZ+2ds1tg/Y1NjEURERES5EosgIiIiypVYBBEREVGuxCKIiIiIciWDzE6AiIiItO/9+/dISEhQ22ZsbIznz58ren92iDUzM4OBwZeXMiyCiIiIcpj379/j5cuXUKlUEARB3p4nTx4YGxsr6iOrx0qSBFEUYW5u/sWFEG+HERER5TAJCQmpCqCcRhAEqFSqVFe7NMErQUREpJhqfeRHr0yBMx9ei93tMychSldOLoBSfO1n5JUgIiIiypVYBBEREVGuxCKIiIiIciWOCSIiIsoF1Mdz6V52GCeWbhHk5+encWeCIOCXX375qoSIiIiIvoV0i6BTp06lGnX9+vVrPH36FACgUqkAAKIoAgAsLS1hamqqmyyJiIgox2vWrBlcXV2RP39+/PrrrxAEAR06dMC0adOgp6f9ETzp9nj16lVcuXJF/goICICRkRFGjhyJ27dv4+7du7h79y5u376NESNGIE+ePAgICNB6gkRERJR77NixA/r6+jh8+DB++uknLF++HDt37tTJvhSXVaNGjUKDBg0wbtw4FCxYUN5esGBBjB8/HvXr18eoUaN0kiQRERHlDi4uLhg/fjyKFSsGLy8v1KxZEydPntTJvhQXQX/99RfKlCmTbnvp0qXx119/aSUpIiIiyp1KlSql9trW1hYxMTE62ZfiIqhAgQI4cuRIuu1HjhxB/vz5tZIUERER5U6GhoZqrwVBgCRJOtmX4iKoW7duOHToEDp06IBjx47JY4KOHj2K9u3b48iRI+jevbtOkiQiIiLSNsXzBI0cORJv3rzBkiVLcOjQIfVODAwwdOhQjBw5UusJEhEREemCRpMlTpgwAf369cOJEyfw4MEDAICDgwPq1KkDCwsLnSRIREREpAsazxhtYWGBNm3a6CIXIiIi0hGxuz0SExNhbGysKF5XsRn5888/U21bvnz5V/ebHq4dRkRERLlSuleCChQokGrG6M8RBAGxsbFfnRQRERGRrqVbBI0aNUrjIoiIiIgou0i3CBo7duy3zIOIiIjom+KYICIiIsqVNCqCnj17hkmTJqFq1aqws7ODnZ0dqlatiilTpuDZs2e6ypGIiIhI6xQXQQ8fPkTNmjWxZMkSmJiYoEWLFmjRogVMTU2xaNEi1KxZEw8fPlS84/nz56Nu3bpwcHDA999/Dx8fH1y/fl0tRpIk+Pv7w9XVFba2tmjWrBlu3LihFiOKIvr06QNHR0c4OjqiT58+EEVRLebatWto2rQpbG1tUaJECcyaNUtnU3ATERFlNgMDAyQkJOTo33WSJCEhIQEGBhrP9iNT/M4pU6bg+fPn2Lt3L2rUqKHWdu7cObRv3x5Tp07F6tWrFfV35swZ9OzZExUqVIAkSfjpp5/QqlUrhISEoECBAgCARYsWYenSpVi6dCmcnZ0xe/ZseHt748KFCzA3NwcA9OrVCw8fPkRgYCAAYNCgQfD19cX27dsBAC9evIC3tzeqVauG48ePIzw8HH5+fjA1NcXAgQOVfnwiIqJsw8zMDG/evMGLFy/Utr948QL58uVT1Ed2iDU2NkaePHkU9ZUWxUXQ8ePH4evrm6oAAoBq1aqhT58+WLduneId79y5U+31ypUr4ejoiODgYDRp0gSSJGH58uUYMmQIvLy8AHyYMMnZ2RmBgYHo3r07wsLCcPToURw8eBDu7u4AgAULFqBJkyYIDw+Hs7MzduzYgdevX2P58uUwMTFByZIlcevWLSxbtgwDBgzgE3BERJQj5cmTJ1WB8OTJEzg4OCh6f3aL/RKKb4e9fv0alpaW6bZbWlri9evXX5xIfHw8kpOToVKpAAD37t1DdHQ0PD095RgTExNUq1YNISEhAIDQ0FDkzZsXVapUkWOqVq0KMzMztRgPDw+YmJjIMfXq1UNUVBTu3bv3xfkSERFR9iaIoqjohmHdunWhp6eH/fv3p6os3759i8aNGwP4cMXoS3Tr1g23b9/GiRMnoK+vj5CQEDRq1AhXr15VqwL9/PwQFRWFnTt3Yt68edi4cSP+/vtvtb7KlSuHrl27YtiwYfD29oadnR2WLl0qtz948ABlypTB4cOH5StInwoPD/+iz0FElFVUPmOaatuFGq+03qc2+iXSNmdn58/GKL4dNmTIEHTr1g1169ZFjx49UKxYMQAfioX169fj5s2b2LBhwxclOm7cOAQHB+PgwYPQ19f/oj607eODl3JrTQnG6i42s/fP2Kyxf8ZqEHsmMtWmz/X9JX1qpd9cEJvZ+2dsaoqLIC8vL6xYsQKTJk3CyJEj5bE0kiTB2toay5cvR4sWLTTaOfBhUsadO3di7969KFKkiLzdxsYGABATE6N2JSgmJgbW1tYAAGtra8TGxkKSJLV8nj59qhYTExOjts+U1ykxRESkfar1HxdMpnIBJXa3z5yEiD6h0XNlPj4+aNOmDS5duoQHDx4AABwcHFC+fPkvekRt9OjR2LVrF/bu3YvixYurtTk5OcHGxgZBQUGoUKECgA+r1J4/fx7Tpk0DALi7uyM+Ph6hoaHyuKDQ0FAkJCTIr93d3TFlyhS1FW6DgoJQqFAhODk5aZwzERER5QwaVy4GBgaoXLkyKleu/FU7HjFiBLZv345NmzZBpVIhOjoawIfH+vLmzQtBENCvXz/Mnz8fzs7OKFasGObOnQszMzO0bdsWAODi4oL69etj6NChWLhwIQBg6NChaNSokXxJrG3btpg1axb69++PESNG4N9//8XChQu5NhoREVEup3ERdPPmTUREREAUxTQnYerQoYOiftasWQMA8uPvKUaPHi2vWzZ48GC8fv0aI0eOhCiKqFixInbu3CnPEZTSz6hRo9CmTRsAQJMmTTB79my5PX/+/Ni1axdGjBiBunXrQqVSwc/PDwMGDNDsgxMR5WD/3bribSvKPRQXQXfv3kWfPn1w8eLFdGegFARBcRH06azO6fU3duzYDBdzValUWLVqVYb9lCpVCgcOHFCUFxFRVpbWOBsWK0RfRqOnw65fvw5/f394eHjI8/kQEdHXYWFDlDkUF0EhISEYNmwYfH19dZkPERER0TeheMZoCwsLxWt9EBEREWV1iougHj16ICAgAElJSbrMh4iIiOibSPd22K5du9ReFy1aFO/fv0f16tXRoUMH2Nvbpzm7s7e3t/azJCIiItKydIugHj16QBAE+Umwj/89ZcqUNN8jCAKLICIiIsoW0i2C9u7d+y3zICIiIvqm0i2CatSo8S3zICIiIvqmNF/w6yNv3rzB3r178fz5czRq1AiFCxfWVl5EREREOqX46bCRI0eidu3a8uukpCQ0adIEffr0wYgRI+Dh4YFr167pJEkiIiIibVNcBB09ehT16tWTX+/atQuXLl3C3LlzceTIEVhYWGDOnDk6SZKIiIhI2xTfDouOjkaRIkXk13/++SdKly6NHj16APjwNNmKFSu0niARERGRLii+EmRkZITXr18DACRJwqlTp9SuDKlUKsTFxWk/QyIiIiIdUFwElSxZEgEBARBFEb/99huePXuGBg0ayO3379+HpaWlTpIkIiIi0jbFt8NGjx4NHx8ffPfddwCAqlWronr16nL7oUOHUKFCBe1nSERERKQDioug2rVr4+TJkwgKCkK+fPnQunVrue3Zs2eoUaMGmjVrppMkiYiIiLRNo3mCXFxc4OLikmp7gQIF4O/vr7WkiIiyO9X6yI9emQJnIiF2t8+0fIgoNY0nSzxx4gROnz6NmJgYDBgwAMWLF0d8fDz+/vtvlCpVCiqVSgdpEhEREWmX4oHRr1+/Rps2bdC6dWssWLAAmzZtQlRUFIAPT4517doVK1eu1FmiRERERNqkuAiaPn06zpw5g1WrVuHq1avyivLAhyKoVatWOHjwoE6SJCIiItI2xUXQH3/8gV69eqFt27YwMTFJ1e7s7IyIiAht5kZERESkM4rHBMXGxqY5KDqFIAhITEzUSlJERFlRWoOdAXDAM1E2pbgIKly4MMLCwtJtDw4OlucQIiIi0gQLTMoMim+HtWvXDhs2bMD58+flbYIgAADWrl2LP/74Ax06dNB+hkREREQ6oPhK0LBhw3Dx4kU0b94cxYoVgyAIGDNmDOLi4hAdHY3GjRujf//+usyViIiISGsUF0FGRkbYsWMHduzYgT/++AOCIOD9+/coV64cvL294ePjI18ZIiIiIsrqFBVBr1+/xuLFi1G5cmW0a9cO7dq103VeRERERDqlaEyQiYkJFixYgIcPH+o6HyIiIqJvQvHA6NKlS+POnTu6zIWIiIjom1FcBE2cOBEbNmzAoUOHdJkPERER0TeheGD0L7/8ggIFCqBDhw6ws7NDkSJFUs0cLQgCAgICtJ4kERERkbYpLoJu3rwJQRBQuHBhAMD9+/dTxfDpMCIiIsouFBdBV69e1WUeREREinB2adIWxWOCdOHs2bNo3749SpQoAZVKhc2bN6u19+vXDyqVSu2rfv36ajFv3rzByJEj8d1338HOzg7t27dHZGSkWsyDBw/g4+MDOzs7fPfddxg1ahTevn2r889HREREWZfiK0EpXr58iQcPHkAURUiSlKq9evXqivtKSEhAyZIl0aFDB/Tt2zfNmDp16mDlypXyayMjI7X2sWPHYv/+/Vi7di0KFCiA8ePHw8fHBydPnoS+vj6SkpLg4+ODAgUKYP/+/Xj27Bn69esHSZIwZ84cxbkSERFRzqK4CIqLi8PIkSOxZ88eJCUlpWqXJAmCICAuLk7xzhs2bIiGDRsCQLpLbuTJkwc2NjZptj1//hy//fYbli5dirp16wIAVq5ciTJlyuDEiROoV68ejh8/jhs3buDq1avyeKapU6di0KBBmDhxIvLly6c4XyIiIso5FBdBgwYNwsGDB+Hr6wsPDw+oVCodpvWf8+fPo1ixYsifPz+qV6+OiRMnwsrKCgBw+fJlvHv3Dp6ennJ84cKF4eLigpCQENSrVw+hoaFwcXGRCyAAqFevHt68eYPLly+jVq1a3+RzEBERUdYiiKKY+p5WGuzt7dGzZ09MmzZNJ4nY29tj9uzZ6NSpk7zt999/h4mJCZycnHD//n3MmDEDycnJOHHiBPLkyYMdO3agb9++ePr0qdqTaS1atMD333+PhQsXYvDgwbhz5w727t0rt0uSBEtLS6xcuRJt27ZNM5/w8HCdfE4iyloqnzFNc/uFGq+0HptWXHaL/ZbHSxuxlHs5Ozt/NkbxlSATExM4Ojp+VUKaatOmjfzvUqVKwc3NDWXKlMGhQ4fQsmVLne7744MXHh6u6GAyVrexmb1/xmaN/Ws99kxkmpvTfM9XxqabR3aK/YbHSyuxH8ns78fM3j9jU1P8dNgPP/yAffv2adS5thUqVAh2dnby8h3W1tZISkpCbGysWlxMTAysra3lmJiYGLX22NhYJCUlyTFERESU+6R7JejixYtqr5s3b44zZ86gdevW6Ny5MwoXLgx9ff1U76tYsaL2s/x/sbGxiIqKkgdKu7m5wdDQEEFBQfLK9pGRkQgLC0OVKlUAAO7u7pg7dy4iIyNhb/9hDomgoCDkyZMHbm5uOsuViIiIsrZ0i6D69eunmgE65ZH4EydOpIr/kqfD4uPj5as6ycnJePjwIa5cuYICBQqgQIEC+Pnnn9GyZUvY2Njg/v37mDZtGqysrNC8eXMAQP78+fHjjz9i8uTJsLKykh+RL1WqFOrUqQMA8PT0RIkSJdC3b1/MmDEDz549w6RJk9ClSxc+GUZERJSLpVsELV26VOc7v3TpElq0aCG/9vf3h7+/Pzp06ID58+fj+vXr2LZtG54/fw4bGxvUrFkT69evh7m5udp79PX10b17dyQmJqJWrVpYsWKFfJVKX18f27dvx4gRI9C4cWMYGxujXbt2mD59us4/HxEREWVd6RZBHTt2xIMHD2BpaZlqoVRtqVmzJkRRTLd9586dn+0jT548mDNnToYTHzo4OGD79u1fkiIRERHlUBkOjC5XrlymD4YmIiIi0oUMH5FPa1kMIiKi7IKLrVJGMnUBVSIiIqLM8tki6NMnxIiIiIhygs/OGL1o0SLFg4oFQUBAQMBXJ0VERESka58tgqKiovD8+XNFnfGqERFlBRwHQkRKfLYI8vf3l2djJiIiIsopODCaiIiIciUWQURERJQrsQgiIiKiXCnDMUF79+6Fi4vLt8qFiIiI6JvJsAiqUaPGt8qDiIiI6Jvi7TAiIiLKlVgEERERUa7EIoiIiIhypc9OlkhERJQbpDXTOGcZz9k0LoJu376NM2fOICYmBu3atYOTkxPevn2L6Oho2NjYwMjISBd5EhEREWmV4iIoOTkZQ4cOxW+//QZJkiAIAipXriwXQdWrV8fIkSMxcOBAXeZLREREpBWKxwTNmzcPmzZtwvjx43HkyBFIkiS35c2bFy1atMC+fft0kiQRkWp9pPxV+Yyp/G8ioi+luAjavHkzOnfujOHDh+O7775L1V6yZEncvn1bq8kRERER6YriIujRo0eoWLFiuu0mJiaIj4/XSlJEREREuqa4CLK2tsb9+/fTbb98+TIcHBy0khQRERGRrikuglq2bIl169ap3fISBAEAcOTIEWzbtg2tWrXSeoJEREREuqC4CBozZgwKFy6MWrVqoXfv3hAEAfPnz0f9+vXh4+OD0qVLY9iwYbrMlYiIiEhrFBdB+fLlw+HDhzFs2DA8efIExsbGCA4ORkJCAsaMGYP9+/fDxMREl7kSERERaY1GkyUaGxtj+PDhGD58uK7yISIiIvomuHYYERER5UoaXQkKCwvD5s2bERERAVEU1SZMBD4MlN6zZ49WEyQiIiLSBcVF0LZt2+Dn5wdDQ0MUK1YMKpUqVcynRRERERFRVqW4CPr5559RtmxZBAYGwsLCQpc5EREREemc4jFBjx8/RufOnVkAERERUY6g+EpQqVKlEBUVpctciCgX+m8RVFPgzId/i93tMy8hIso1FF8JmjlzJjZt2oTg4GBd5kNERET0TaR7Jahdu3aptpmbm6Np06YoVqwYChcuDH19fbV2QRAQEBCg/SyJiIiykP+uYAIpVzF5BTP7SfdK0M2bNxEWFqb29ebNGxQuXBiJiYn4999/U7XfvHlTo52fPXsW7du3R4kSJaBSqbB582a1dkmS4O/vD1dXV9ja2qJZs2a4ceOGWowoiujTpw8cHR3h6OiIPn36QBRFtZhr166hadOmsLW1RYkSJTBr1iw+yUZERJTLpXsl6OrVqzrfeUJCAkqWLIkOHTqgb9++qdoXLVqEpUuXYunSpXB2dsbs2bPh7e2NCxcuwNzcHADQq1cvPHz4EIGBgQCAQYMGwdfXF9u3bwcAvHjxAt7e3qhWrRqOHz+O8PBw+Pn5wdTUFAMHDtT5ZyQiIqKsSfGYoLNnz+Lp06fptsfGxuLs2bMa7bxhw4aYNGkSvLy8oKennookSVi+fDmGDBkCLy8vlCxZEsuXL0d8fLxc8ISFheHo0aNYuHAh3N3d4e7ujgULFuDQoUMIDw8HAOzYsQOvX7/G8uXLUbJkSXh5eWHw4MFYtmwZrwYRERHlYoqLoBYtWiAoKCjd9pMnT6JFixZaSQoA7t27h+joaHh6esrbTExMUK1aNYSEhAAAQkNDkTdvXlSpUkWOqVq1KszMzNRiPDw81BZ3rVevHqKionDv3j2t5UtERETZi+JH5D931eTt27epruZ8jejoaACAlZWV2nYrKyv5Uf0nT57AwsICgiDI7YIgwNLSEk+ePJFj7OzsUvWR0lakSJE0959yJSm91xlhrO5iM3v/jNVFn6YK35M6LrvFpn8sslNs1jy2uorVzrHVLIax2ol1dnb+bHyGRdCLFy/w/Plz+XVcXBwePHiQKk4URQQGBqJQoUKKE83qPj544eHhig4mY3Ubm9n7Z6yO+jwTmWpTmu9JIy67xaZ7LLJTbBY9trqK1cqx/X+Z/X+XsallWAQtW7YMs2fPBvDhCsvYsWMxduzYNGMlScKUKVM02nlGbGxsAAAxMTFwcHCQt8fExMDa2hoAYG1tjdjYWEiSJF8NkiQJT58+VYuJiYlR6zvldUoMERER5T4ZFkGenp4wMzMDAEyaNAlt27ZF2bJl1WIEQYCZmRnKly8PNzc3rSXm5OQEGxsbBAUFoUKFCgCAxMREnD9/HtOmTQMAuLu7Iz4+HqGhofK4oNDQUCQkJMiv3d3dMWXKFCQmJsLY2BgAEBQUhEKFCsHJyUlr+RLRfzgLNBFlBxkWQSlPXAEfHmdv2bIlSpYsqbWdx8fH486dOwCA5ORkPHz4EFeuXEGBAgXg4OCAfv36Yf78+XB2dkaxYsUwd+5cmJmZoW3btgAAFxcX1K9fH0OHDsXChQsBAEOHDkWjRo3kS2Jt27bFrFmz0L9/f4wYMQL//vsvFi5ciFGjRqmNJSIiIqLcRfHA6DFjxmh955cuXVJ7oszf3x/+/v7o0KEDli9fjsGDB+P169cYOXIkRFFExYoVsXPnTnmOIABYs2YNRo0ahTZt2gAAmjRpIt/CA4D8+fNj165dGDFiBOrWrQuVSgU/Pz8MGDBA65+HiIiIsg/FRZAu1KxZM9Xszh/73DgkAFCpVFi1alWG+ylVqhQOHDjwpWkSERFRDqS9Z9qJiIiIspFMvRJERNkHBzsTfRn+38m6eCWIiIiIcqVMXTuMiIiIKLNk2bXDiIiIiHRJcRH0rdcOIyIiItIlrh1GREREuVKWXTuMiIiISJey7NphRERERLqUqWuHEREREWWWTF07jIiIiCizaDxjdEhICC5fvowXL14gOTlZrU0QBIwaNUpryRERERHpiuIiSBRF+Pj44MKFC5AkCYIgyI/Np/ybRRBR9vLfdP5AypT+nM6fiHILxRP7TJ48GVeuXMGqVatw+fJlSJKEnTt34uLFi+jSpQvKli2LW7du6TJXIiIiIq1RXAQdOnQIXbp0Qdu2bWFubv7hzXp6+O6777Bw4UIUKlQI48aN01miRERERNqkuAh69uwZSpUqBQAwNDQE8OGJsRQNGjTA0aNHtZweERERkW4oLoKsra3lBVTNzc1hbm6O8PBwuf3Zs2dISkrSfoZEREREOqB4YHTlypVx/vx5+XX9+vWxZMkS2NraIjk5GcuWLZPnFCIiIiLK6hRfCerduze+++47JCYmAgCmT5+OggULom/fvujfvz8KFiyIn3/+WWeJEhEREWmT4itBHh4e8PDwkF/b29sjODgY165dg76+PooXLw4DA42nHSIiIiLKFF9Vtejp6aFMmTLayoWIiChX+2/urg/zdgHg3F06pPh2GBEREVFOwvtXRDkMZ4EmIlKGV4KIiIgoV2IRRERERLkSiyAiIiLKlTQeE3T79m2cOXMGMTExaNeuHZycnPD27VtER0fDxsYGRkZGusiTiIiISKsUF0HJyckYOnQofvvtN0iSBEEQULlyZbkIql69OkaOHImBAwfqMl8iIiIirVB8O2zevHnYtGkTxo8fjyNHjkCSJLktb968aNGiBfbt26eTJImIiIi0TfGVoM2bN6Nz584YPnw44uLiUrWXLFkShw4d0mpyRPRBWo+9A5xEjYjoayi+EvTo0SNUrFgx3XYTExPEx8drJSkiIiIiXVN8Jcja2hr3799Pt/3y5ctwcHDQSlJERESUMS6x8fUUXwlq2bIl1q1bh9u3b8vbBEEAABw5cgTbtm1Dq1attJ4gERERkS4oLoLGjBmDwoULo1atWujduzcEQcD8+fNRv359+Pj4oHTp0hg2bJhWk/P394dKpVL7Kl68uNwuSRL8/f3h6uoKW1tbNGvWDDdu3FDrQxRF9OnTB46OjnB0dESfPn0giqJW8yQiIqLsR3ERlC9fPhw+fBjDhg3DkydPYGxsjODgYCQkJGDMmDHYv38/TExMtJ6gs7MzwsLC5K9z587JbYsWLcLSpUsxa9YsHD9+HFZWVvD29sbLly/lmF69euHKlSsIDAxEYGAgrly5Al9fX63nSURERNmL4jFBkZGRsLe3x/DhwzF8+PA0Y06fPo2aNWtqLTkAMDAwgI2NTartkiRh+fLlGDJkCLy8vAAAy5cvh7OzMwIDA9G9e3eEhYXh6NGjOHjwINzd3QEACxYsQJMmTRAeHg5nZ2et5kpERETZh+IrQV5eXoiJiUm3/fDhw/Dx8dFKUh+LiIiAq6srypYtix49eiAiIgIAcO/ePURHR8PT01OONTExQbVq1RASEgIACA0NRd68eVGlShU5pmrVqjAzM5NjiIiIKHdSfCVIX18fXl5e2LdvHwoWLKjWtnv3bvTu3Rt16tTRanKVKlXCsmXL4OzsjKdPn2LOnDlo2LAhgoODER0dDQCwsrJSe4+VlRWioqIAAE+ePIGFhYU8gBv4MJjb0tIST548yXDf4eHhGb7W5L2M1V5sZu9fm7GVz5h+9Oq/pzsu1HiVRrRpGtvS6z91bPp5ZKfYrzsGWSE26x5bTWKz5rHVVWzWPQ+axmoWkxNildztUVwE/fHHH2jatCm8vb2xZ88e5M+fHwCwZcsWDBo0CE2bNsXatWsVJ6pEgwYN1F5XqlQJbm5u2LJlCypXrqzVfX3q44Onya0zxuouNrP3r/XYM5Fpbk7zPV8Zm24e2Sn2Gx4vXcVm2WOrSWwWPba6is2y50HT2P+XLX42foPYFIpvhxUqVAi7d+9GbGws2rZti/j4eKxatQoDBgxAu3bt8Ouvv8LQ0FCjnWsqb968cHV1xZ07d+RxQp/eoouJiYG1tTWAD3MbxcbGqi3xIUkSnj59KscQERHlZKr1kfJX5TOm8r9JgyIIABwdHbFnzx48fPgQNWvWxJgxY9CjRw8sX74cenoadfVFEhMTER4eDhsbGzg5OcHGxgZBQUFq7efPn5fHALm7uyM+Ph6hoaFyTGhoKBISEtTGCREREVHuk+7tsPQGQZubm2PVqlXo2LEjOnbsiNGjR6vFfjpG52tMmDABjRs3RuHCheUxQa9evUKHDh0gCAL69euH+fPnw9nZGcWKFcPcuXNhZmaGtm3bAgBcXFxQv359DB06FAsXLgQADB06FI0aNeKTYaQTXOOLiCj7SLcIKl68uNqA4k9JkoQtW7Zgy5YtatvTWlz1Sz169Ai9evVCbGwsLC0tUalSJRw5cgSOjo4AgMGDB+P169cYOXIkRFFExYoVsXPnTpibm8t9rFmzBqNGjUKbNm0AAE2aNMHs2bO1liMRERFlT+kWQaNGjcqwCPoW1q1bl2G7IAgYO3Ysxo4dm26MSqXCqlWrtJ0aERERZXPpFkEZFRZERERE2Z3uRzMTERERZUHpXgnaunUrAKB9+/YQBEF+/TkdOnTQTmZEREREOpRuEdS/f38IgoA2bdrAyMgI/fv3/2xngiCwCKIch098ERHlTOkWQX///TcAwMjISO01ERERUU6QbhGU8hh6eq+JiIgoZ8ltV74Vrx32sX/++Qf3798H8KE4Kl26tFaTIiIiItI1jYqgP/74AxMnTkRk5IfKUJIkCIIAOzs7TJs2Da1bt9ZJkkS68N9fPDn/rx0iIkpNcRG0bds29OvXD87Ozpg6dSqKFSsGAPj333+xceNG9OrVC2/fvkX79u11liwRERGRtigugubOnYuKFSti3759MDY2Vmvr3bs3mjZtirlz57IIIiIiomxB8WSJDx8+RLt27VIVQABgbGwMHx8f+TYZERERUVanuAhydXVFVFRUuu2PHj2Ci4uLVpIiIiIi0jXFRdC0adOwYcMG7Nq1K1Xb77//jo0bN2L69OlaTY6IiIhIVxSPCVqyZAksLCzQs2dPjBkzBkWLFgUA3L17FzExMfj++++xePFiLF68WH6PIAgICAjQftZEREREX0lxEXTz5k0IgoDChQsD+HD7CwDy5MmDwoUL482bNwgLC1N7jyAIWkyV6PP42DsR0beREyZWVFwEXb16VZd5EBEREX1TXzRjNNG3xKs7RESkC19cBJ0+fRoBAQF4/Pgxihcvjr59+8LBwUGbuRERERHpTIZPh/38888oVKgQnj59qrZ98+bN8PLywqZNm3D06FEsW7YMnp6e8npiRERERFldhkXQ6dOn4enpCUtLS3nbmzdvMHbsWOTLlw+7d+/Gw4cPsW7dOsTHx2P+/Pk6T5iIiIhIGzIsgu7cuQM3Nze1bSdPnsTLly8xaNAg1KpVC2ZmZvD29sYPP/yAEydO6DBVIiIiIu3JcEzQs2fPYGtrq7bt9OnTEAQBjRo1Utvu5uaG7du3az9DypHSerSSg52JiHKmrPo4fYZXgmxsbFItlXH+/HmYmprC1dVVvSM9PRgZGWk/QyIiIiIdyLAIqlixIrZu3QpRFAEA//zzDy5duoTatWtDX19fLTYsLAz29vxLPjdTrY+UvyqfMf2k8iciIspaMrwdNnr0aNSuXRsVK1aEi4sLrl69CkEQMGTIELU4SZKwb98+eHp66jJXIiIiIq3J8EqQi4sL9uzZg4oVK+Lp06eoUqUKdu7cicqVK6vFnT59Gnnz5kXLli11mix9e7y6Q0REOdVnJ0t0d3f/7CKotWrVwrlz57SWFBEREZGuZXgliIiIiCin4tphuVBWfVSRiIjoW06hwitBRERElCuxCCIiIqJcibfDcgje4iIiotzma2+d8UoQERER5Uq56krQmjVrsHjxYkRHR8PV1RX+/v6oVq3aN81Bkys2vLpDRESkO7nmStDOnTsxZswYDB8+HKdOnYK7uzvatWuHBw8eZHZqRERElAlyTRG0dOlSdOzYEV27doWLiwvmzJkDGxsbrFu3Tiv9fzqrMmdWJiIiytoEURSlzE5C196+fYtChQph7dq1aNWqlbx9xIgRuH79Ovbv3595yREREVGmyBVXgmJjY5GUlAQrKyu17VZWVnjy5EkmZUVERESZKVcUQURERESfyhVFkIWFBfT19RETE6O2PSYmBtbW1pmUFREREWWmXFEEGRkZwc3NDUFBQWrbg4KCUKVKlUzKioiIiDJTrpknyM/PD76+vqhYsSKqVKmCdevW4fHjx+jevXtmp0ZERESZINcUQa1bt0ZcXBzmzJmD6OholChRAgEBAXB0dMzs1IiIiCgT5IpH5LOrpKQkxMbGAvhvXBNlbTxnuqPJsdUk9v79+/JTotbW1un+YaSr/efkWE0oPQ+Z3acu+9akT11+ttwk11wJUioyMhLr1q1DSEiI2jdY1apV0a1bNxQuXFiO/d///ofly5eniq1SpQr69++P8uXLf1Hs3r178csvv+DSpUt4//49AMDAwADly5fHwIED0bx5c4371VWuWSGW5yz7xWpyzjQ5tprELl26FMuWLUNUVBQk6cPfgoIgoFChQvDz80P//v11uv+cHPuxz/2yVnoedN2nkn6/pu+MaNKnLvb/KV0UxVm1KOeVoI+cP38e7dq1g42NDTw9PeV5hWJiYhAUFITo6Gjs2LEDVatWxb59+9CtWzfUqFED9erVSxV75swZrF+/Hs2aNdModv369Rg1ahQ6dOiQKvb48ePYtm0bZs+eja5duyruV5IkneSaFWJ5zrLGedDVOdPk2GoSO3v2bCxZsgSDBw9OM3bRokUYOHAgLC0tdbL/nBybQskva6XnYeTIkTrrU2m/AL6o7/j4eFy+fFmtuHJzc0PevHk17vNL9q+rP+aUxma1ojwVURQlfn34cnNzk/r06ZNuu6+vr1S+fHlJFEWpRIkS0sSJE9ONnTRpkuTq6qpxbNGiRaXFixenG7t48WKpSJEiGvWrq1yzQizPWdY4D7o6Z5ocW01i7e3tpY0bN6Ybu3HjRqlQoUI6239OjhVFURo3bpxkbm4uTZgwQQoKCpL++ecf6Z9//pGCgoKkiRMnSvny5ZPGjx+v+Dzoqk9N+tXk+0YURenp06eSr6+vZGJiIgmCIBkYGEgGBgaSIAiSiYmJ1LdvXykmJkajPjX9bJs2bZIMDAykOnXqSNOnT5dWrFghrVixQpo+fbrk6ekpGRkZSZs3b5ZEUZQWLFggGRoaSl26dJE2bNgg7d+/X9q/f7+0YcMGqWvXrlKePHmkRYsWaRSriz41jf3cF68EfcTW1hanT5+Gs7Nzmu23bt1CrVq18PjxY9jY2ODMmTPpxoaHh6NGjRqIjo7WKFYXOQDQSa5ZIZbnLGucB10dL13FFipUCCdOnICLi0uasTdu3ICnpyckScr0XLNbLACUKlUK/v7+aNmyZZrxe/bswejRoyGKoqLzEBUVpZM+Ncn1xo0bir9voqKiMHr0aOzZswdTp05FvXr1YGFhAeDDCgbHjx/H5MmT4eXlhV9//VVxn5rsHwA8PDzQtm1bDB8+PM34+fPnIyAgAMHBwShfvjyGDh2KLl26pBm7ceNGzJ8/H5cvX1YcKwiC1vvUNPZzcsU8QUrZ2NggODg43fbg4GDY2NgAAIoWLYp9+/alG/vnn3+iSJEiGse6urpi7dq16cauX78erq6uGvWrq1yzQizPWdY4D7o6Z5ocW01iK1SogNmzZ+Pt27ep4t6+fYt58+ahQoUKOtt/To4FgLi4uHR/UQOAs7MzRFFUfB501acm/QLKv28AIDAwECtWrMAPP/wgF0DAh3Er7dq1w7JlyxAQEKBRn5p+tjt37qRb3AFAixYtcPfuXQBAVFQUPDw80o2tWrWqXOQqjdVFn5rGfg4HRn9k4MCBGDZsGP73v/+hTp068mzST548wYkTJ7Blyxb4+/sDAMaOHYuePXvi9OnTqFu3bqrYU6dOyT80NImdMWMGfHx8cPTo0TRjo6KiEBAQoFG/kiTpJNesEMtzljXOg67OmSbHVpPYOXPmwNvbG8WKFYOHh4da7Pnz52Fqaopdu3YhNjZWJ/vPybHAf7+sly9fDiMjI3zs41/WSs+DrvrUpF9Nvm8AIDExEQULFkR6ChYsiMTERI361PSzpfxxMnTo0DRzSOuPuZ9//jnN2LSKYiWxuuhTk9jP4e2wT+zcuRPLli3D5cuXkZSUBADQ19eHm5sb/Pz84O3tLceGhoZixYoVCA0NVRtw5u7ujr59+8Ld3f2LYu/du4d169bhwoULqWK7d+8OJycnjfvVVa5ZIZbnLPvFanLONDm2msS+fPkSAQEBaca2bdsW+fLl0+n+c3Ls9evX4e3tjdevX2f4y7pEiRKKz4Mu+tS0X02+b3x8fPDq1SusWrUKhQoVwseioqLQt29fmJiYYNu2bRrlq0ns7t270bNnT9SqVSvDP05atmyJM2fOwMfHB4UKFcqw0K1WrZri2OTkZK33qWns57AISse7d+/UHrszNDTM5Izoc3jOsh+es5xLk1/Wmdmnrvp9+PAhfvjhB4SFhcHFxUXtSa6wsDC4uroiICAA9vb2X5SzUrr6Y05pbFYoyjPCIoiIiEgHkpOTcezYsTR/UXt6ekJPj8NyMxvPgAbWrFmD2bNnK4qdPn06BgwYoPXYvn37ZjjQ7Uv61VWuWSGW5yz7xWpyzjQ5tprEenl5wc3NLdP2n5NjNaH0PGR2n+n1raenhwYNGmDcuHFYuHAhFi5ciHHjxqF+/fqKCyBN8tXlZ8upODBaAytXrsTt27cxatSoz8ZeuHAB9+7dU9SvJrGSJCE5OVmr/eoq16wQy3OW/WI1OWeaHFtNYitUqKDoNoWu9p+TY4EPv6zv3bv32UeYlZ4HXfWpSb9f0rcSmvSp6f6nT5+O6Oho/PLLL5+N7du3Lx49eoQ9e/ZoLVYXfWoay9thRET0TU2dOhXR0dFYtmzZN+vz3bt3XzTmTBe5AoC7uztu374tj4nLDC1btsS9e/fw999/fzbW19cXkZGRGU6FoWmsLvrUNJZFEBERfVZG6711795d5wN8v5aVlRXOnDmT4ZxA39KqVasQFxeHMWPGaPS+x48fY+3atQgODkZ0dDT09PTg5OSEZs2aoVOnTly0WUMsgj4hSRJOnDiR5n/02rVrQxAEtfiTJ0+m+mZs2rQpvv/+e7W48+fP4+LFi6hTpw5Kly6Na9euYdWqVUhOTkaLFi3QsGFDAMCSJUvQqlUrODg4fDbXZ8+ewcDAAObm5gCAa9euYf369Xjw4AEcHR3RrVs3lCpVKs33XrlyBXfu3IGNjQ2qVq2a6nN9qkmTJlixYkWqEfdJSUmIiIiAo6MjDA0NkZiYiD179uDNmzdo3Lix/EREivj4eJiamqa6H/7u3TuEhoaievXqn/3coijiwIED6NChAwCes/TklHP2+vVrBAYGpjpnzZs3R+3atdX2ExAQgL/++gsNGjRAgwYNcPz4cSxZskQ+Z7169QIAjBw5Eq1bt85wwjXgw0zXZmZmsLOzAwAcOXIEq1evxsOHD+Hg4IDevXujfv36ab733bt3OHTokHzOmjdvDjMzswz3V7p0aezevTvV9+LTp09x9epVlClTBpaWlnjy5Ak2btyIN2/ewNvbGyVLlpRjk5OTERYWBpVKlerR7MTEROzatUs+Dxl58uQJ1q9fj9GjR2u03psSDx8+hL+/P5YuXQpRFBESEgKVSgV3d3e1c5+QkIBffvkFo0ePBvDhcfYLFy7A3d0dJUqUwM2bN7Fs2TK8efMGPj4+8PT0TPc26po1a9C2bVuoVCoASHfcmSiK2LJli3zeOnToIC/oe+7cOVhZWckzZ69ZswZr1qxR+37o0aOHomOQIjk5GfPnz8dff/2FRo0aoXv37ti0aRMWLFggf99OmDABRkZGuHTpEry8vPDdd9/BxMQEoaGhaNu2Ld69e4djx47B1dUVgYGB8s8X+jwWQR959OgRfHx8cO3atTQfaSxTpgy2bt0KOzs7xMTEoH379rh06RL09PSQnJyMsmXLIioqCk+fPoWfnx+mTZsGANixYwd8fX1hb2+PuLg4rFmzBr6+vqhQoQL09fVx4sQJLFu2DD4+PihQoAD09PRQp04ddOvWDU2bNk23sm/cuDEGDBiA5s2b4+TJk2jTpg0qVKgAFxcX/Pvvv7h48SICAwOxceNGLFiwAObm5oiPj0fXrl1x/Phx6OvrIykpCW5ubti1axdUKlW691C7d++OmTNnyr8MWrZsiVu3bsHb2xuPHj2Co6Mjdu/ejS5duuD27duQJAl58uTBkSNHUKxYMTx79gy9evXCiRMnkCdPHnTt2hVTp06VJyd78uQJXF1dERcX99nzdPXqVdSuXRtxcXE8Zzn8nN25cwdeXl5ITExEnjx5EBkZiYYNGyI2NhaXLl1CixYtsGbNGhgYGGDZsmWYOnUqKlWqhH/++QdTp07FhAkT0Lp1a+jr62Pbtm2YMGEC/Pz8UKBAAQiCgGLFiqFr167o0KFDmhPb1alTBxMmTED9+vWxa9cu9O7dG97e3ihevDj+/fdf7Nq1CytXroS3tzcaNmyIgIAAqFQqPH36FC1btkR4eDjs7OwQFRUFa2trHD58GHZ2dumOwZg8eTL8/PzkeU8GDBgg/6J7+fIl8uXLhz/++ANdu3aFoaEhkpOTERUVhQMHDqB8+fJ4+PAh2rVrh5s3b0IQBDRp0gRLly6Vf/F/6TmrU6cO3N3d0y0cRo8ejdDQUAQFBX2234/7Pnv2LFq1aoWnT58iOTkZ5cqVw8aNG+XV2z/O9/Dhw+jUqRPy5s2LV69eYdOmTejbty/KlCmD5ORknD17Fr///ju8vb1RunRp5M+fX22fZ8+eRfny5WFqagpBELB3714AHybeO3fuHAoWLIiIiAg0atQIycnJcHV1RXh4OF69eoWjR4+iePHi8PDwwKxZs1CrVi2sXr0aU6dOha+vL4oXL47w8HCsWrUKEydORO/eveHj44PWrVujVatWyJMnT7rHYsaMGVizZg2aNGmC06dPo0OHDlizZg38/Pygp6eHZcuWoVu3bpgwYQIaN26MOnXqyFePtm/fjtWrV+Po0aMQRREtWrRAtWrVMGvWLLn/hIQEBAYGpvkHR5s2bT5bmKf4uCgGlBfbmhTwaUnvD4OPfckfHDIlC4zllq8mTZpINWrUkK5du5aq7dq1a1LNmjWlpk2bSqIoSq1bt5aaNWsm3b9/X4qOjpZ69+4ttW/fXhJFUdq9e7dUsGBByd/fXxJFUSpdurQ0Y8YMSRRFafPmzZK5ubk0btw4ue/p06dLZcqU+bCYmyBI8+fPl+rUqSPp6elJNjY20tChQ6X//e9/qXIyNzeXt3t4eEjDhw9Xa584caJUqVIlSU9PTwoPD5dEUZQGDhwoOTk5ScePH5eePXsmnT59WnJxcZH69+8v719PT08SBCHdLz09PUkURalp06ZSkyZNpLNnz0r9+vWTXFxcpKZNm0oxMTFSdHS01LhxY+mHH36QRFGUevbsKZUoUULasWOHtHbtWun777+XatWqJT169EgSRVG6deuWJAiCJIqidPXq1Qy/duzYIefAc5azz1mDBg2k7t27S8+ePZNEUZSmTJkiNWjQQBJFUbp48aLk6OgojR49WhJFUXJ2dpZWrlwpiaIoHTp0SDIyMpLmzp0r97106VLJxcVFPmbbt2+XunTpIpmbm0vGxsZSmzZtpN27d6vlY2pqKv3999+SKIpShQoVpJkzZ6q1L1q0SCpdurTcZ8o569q1q1S6dGnp5s2bkiiK0u3btyV3d3epc+fOcqy9vb3k6Oio9iUIgmRnZyc5OjpKTk5OkiiKUu3ataUuXbpIDx48kKZPny7Z29tLXbp0kXPo1KmT1KxZM0kURaldu3aSh4eHFBISIh05ckSqUqWKVLJkSenff/+Vz1nKefjzzz8z/Fq8eLEca2xsLF24cCHdn52hoaGSsbGx/Hr58uUZfo0fP17S09OTGjduLDVv3lyKjIyUbt68KbVq1Uqys7OTLl68mCpfd3d3acSIEZIoitLatWsllUql9v9n6NChUt26daVJkyZJTk5O0r59+9RyNDAwkIKDg1Pl/vF5a9OmjVSjRg0pMjJSEkVRevz4sdSoUSPJy8tLPg5XrlyRRFGUypQpIy1btkytr19//VVydnZW+3+pUqkkX19f6dy5c2keOycnJ2nbtm2SKIpScHCwpKenJ61atUpu/+2336SiRYtKoihKJiYm0uXLl+W2uLg4ydDQULp165YkiqK0a9cutQVUg4ODpUKFCknm5uZSo0aNpM6dO0udO3eWGjVqJOXLl0+ys7NL85ik9XX69Gn5XPzzzz9SiRIl5M/YrFkzKSIiQo5NOW+HDx+W8uXLJwmCIOXPn18KCgqSHB0dpe+//14qWrSoZGxsLAUFBUmiKEozZsxI80tfX18aNGiQ/DrleyFlf//++69UsmRJydDQUHJycpKMjIykwoULS9evX1f0uaAkKLd8mZmZSadOnUq3/eTJk5KZmZkkiqKUL18+6fz583JbZGSkZGhoKN2/f18SRVFauXKl/J/h4x+kz549kwwNDaWzZ8/K7718+bKUN2/eVP8hL1++LA0bNkyytbWV9PT0pJo1a0pr166Vnjx5IomiKOXNm1cKCQmRRFGUrKyspNOnT6vle+nSJSlv3rxqfZYoUUJav369WlxAQID0/fffS6IoSvXr15caNWok3b59Wy0mrR8glpaW8vGKjIyUBEGQDhw4ILcfOnRIKly4sCSKolS4cGFp//79cltERITk4eEhVa9eXXr06JHaD7uU/1jpfX38S53nLGefM1NTU/kXoiiK0pMnTyRDQ0Ppzp07kih+KFAdHR0lUfzwC+Lq1atyrKGhodovnr///lsyNTVNdc4iIyOlhQsXShUqVJAEQZCKFi0qTZ48WQoLC5Py588vnyNLS0vpzJkzqc5XWn0WK1ZM2r59u1rs3r175Vy7desmlS1bNlVhkdY5U6lU8vdMTEyMpKenJx07dkxuP3HihGRnZyeJoijZ2trKv1RS4lu1aiW5uLhI4eHhaZ4zJcWzk5OTtGTJknTP2eLFi+WiLaVvMzMzKW/evGl+mZqaSnp6epKlpaXa/0lRFKX+/ftLhQoVkv766y+1fPPlyyf/AREXFycZGBhIJ0+elN937tw5ydraWhJFUTpy5IhUtGhRadiwYVJcXFy6x/bT8+bk5JSqED569Khkb28vfw+cOHEiw/+/JiYmcr+nTp2SJkyYIBUpUkTS09OTKlWqJC1ZskT+Q0IUPxRWn37ffnxMrly5In+POTg4qP2fvHHjhiQIghQVFSV/j39cjNaoUUPy9vaWHj9+nOpzP378WGrdurVUo0YNSRQ1K4qVFtuaFPCa/GGgyR8cn/viPEEfMTY2xrNnz9JtF0URxsbGAAAjIyO1e9eCICApKUleAqBKlSq4f/8+AMDc3Fy+/CyKIt6/f692OTouLi7NS3dFihTBpEmTcO3aNWzYsAEmJibo06ePPH175cqVsX//fgBAsWLFcPXqVbX3X7lyBQUKFJDzA/67vPwxV1dXREZGAviw6F+NGjVQu3ZtHD9+PMPjlZCQIPdvZmYGMzMz2Nrayu329vaIiYkB8GHl5JTbMgCgUqkQGBiI5ORktGnTBgkJCXJbvnz58NNPP+H48eNpfq1atUqO5TnL2ecsf/78ePnypdz26tUrvH//Xn7Kp1SpUoiOjgbwYS2mlPMXGRmJ9+/f4+HDh/J7Hzx4IH/2j5mZmaFbt244fvw4Tp48CU9PTyxYsAClS5dGrVq1sGPHDgCAm5sbTp8+rfbeU6dOqR2jlHP2/Plz+ZZOCicnJznXhQsXYvjw4WjVqhV+/fXXdI8F8OFSf8rxMDQ0hKmpqdqCnJaWlvL3ZsotsxSGhoZYu3YtXF1d0axZM7VFJS0sLLBixQrcvn07za+Pb7OmrPc2dOhQ7N69G+fPn8f58+exe/duDB06FCNHjsTgwYPl+EKFCmH58uV4+PBhml8HDx4E8GFtrk/Htv30009o1aoVmjdvjrCwMLW2lHFpenp6MDY2VrvllTdvXrx48QLAh/9nJ06cwN27d1GvXj3cvn07w2OcksPbt29TjYmzsrLC06dPAQANGjSQv5dr1qyJP/74Qy12586dardtChUqhBEjRuDy5csIDAyEvb09hg8fDldXVwwdOhSXL1+GjY0Nbty4AeDDGLSkpCS1z33z5k1YWloCAJo1a4Zhw4bh4MGDCAoKQs+ePVG9enWYmJjI7//41tTFixcxevRo+fvnY8bGxhgxYgQuXrwIAGjevDlatGiB5s2bp/n18fk9ffo0fvrpJ7i4uKBy5crYt28fihcvjmbNmsk/PwDg77//hp+fH8zNzdG3b19ERUWha9eucnvv3r1x6dIlAEDXrl1hYWGB33//HVeuXJG/9PX1sXPnTly5ciXNp9jOnj2LiRMnyj/HLCwsMHHiRJw6dSpVbFo4T9BHWrdujX79+mH69OmoW7euPEYgLi4OQUFBmDx5Mtq2bQvgwyq1M2bMwLJly5AnTx5MnjwZRYoUkX/IxsTEyPfha9eujeHDh6NXr174448/0KBBA0ydOhWLFy+Gnp4eJk6cKA8oTGuwq76+Plq0aIEWLVrgwYMH2LRpEwDI4x1evXqF1q1bY+LEibhz5w5cXFwQHh6OlStXYvjw4Zg8eTKmTp0KExMTCIKAx48fy7+UUz7fx7/QBw4ciOrVq6N3795o0KCBPE7mU7a2toiMjJQHBE+dOlX+zwp8GMyZ8kPKwcEBYWFh8mJ9wIdfPoGBgWjbti06deokby9btiwSExPTnfRLX18fkiTxnOWCc1anTh2MHTsW8+bNQ548eTBt2jSUKVNGHvj54MED+ZdW06ZNMWDAAPj4+ODgwYPo2LEjJkyYgOTkZOjp6WHKlCmoW7duuucs5XPMmzcPM2bMwM6dO1GlShU0btwYjx8/RrVq1TBz5kxcunRJPl+7du3CwoUL5ff36dMHRkZGePfuHe7du6d2zqKjo9V+aXt5eaF8+fLo3bs3jhw5giVLlqSZk729Pe7duycPcF+7di1sbGzU+k05hkWKFME///yj9otYX18f69atQ7du3dQGRJcrVw4RERHpLvKpUqnkc9arVy8ULFgQy5Ytw2+//ZZqvbcVK1aorfdWrlw5XLlyJd0JFAVBgCRJKFasGC5dupSqyPf390dycrLa95iDgwNu374tfz8ePnxYHrAMfCh8U8ZSAR8K6PXr12PDhg3yOJ/0NGvWDPr6+njx4gXCw8PVxqk8fPhQLjqnTJmCRo0aoUmTJqhYsSKWLVuGc+fOyWOC/vrrL2zevDnNfXh6esLT0xNPnz7F5s2b8dtvv2HDhg0YNmwY+vbti8aNG+P06dMYNmwYJkyYgCdPnkBPTw8LFy6Uj+OECRMQHR2Nzp07IykpCe7u7mqP7uvp6WHy5Mnya5VKhX///TfdxURv374t/8yzsLDATz/9lO5A/2vXrsHLywtA+sV2jx490KxZM6xZswaAZgX8woULsXv3brRq1QojR45Et27d0swjhdI/OD6HRdBHZs6ciaSkJPTr1w/v37+XB7cmJSXBwMAAP/74I2bMmAHgw2A2b29vFC1aFIIgwMzMDBs2bJD7unXrFjp27CjH+vr6YtSoUfDw8MC6deswffp0VK9eHYIgoGjRovJAyZQfOulxcHDA2LFjAQAVK1bE77//jvHjxyM0NBQAMG/ePAAf/gIZM2YM+vXrh0OHDuHu3bsAPlxBePDggVqfhw8fTvWfpEKFCjhx4gSGDx+OOnXqpJlXrVq1EBYWJhcDPXv2VGs/efIkypUrB+DDL7PNmzejUaNGajFmZmbYsWOH2g/Qtm3b4tWrV+keAxsbG3lwHs/Zf3LiOZs2bRo6duwoH3d7e3u5oAQ+FE4DBw4E8OEX1Nu3b7Fnzx5UrVoVs2bNwooVK9ClSxe8e/cO1atXl39BfO6cmZiYyL+Ajx07hhkzZmDBggVISEjAjh07YGBggAoVKmDdunVo1qwZAKgVGE2bNsXr16/V+tyzZw/KlCmjts3R0RH79+/HTz/9hBo1aqSZl5eXl9oP9E/Px4EDB+RVzuvXr48NGzbIv6xS6OvrY/369ejSpQuioqIAAN26dcvwnDk4OGDp0qXy69atW6N169aK1nsbOHCg2pXCT3333XfYu3cvQkND8fvvv6f5tNqsWbOQlJSEtWvXAvgw0P/t27dy+6cDag8fPowaNWqk6qdr166oXr06QkND1a7apUj5vkyRN29etdcHDx6UnyK0sbHByZMnsWjRIuzfvx+SJOHixYt4+PAhqlatipkzZ6J8+fLpfm7gwy/+wYMHY/DgwTh9+rR8JSc0NBQ9e/bEkCFDUKJECUyePBmvXr1C48aNMX78eDm39evXIzExEe/fv0+Vq6enp9rrLl26oH///ggPD0fdunVTPdW3cOFC9O/fH4BmRbHSYluTAh5Q/ocBoNkfHBnh02FpePHiBS5fvqw2kt7NzS3VInqvXr1CSEgI3rx5g8qVK6tVuEpERETg1atXKF68OAwMPtSj9+/fh4ODw2cff/7U06dPERERgeTkZNjY2ChePC4lD0NDw3Tn+di2bRtOnTqFSZMmqd06+Zy7d+/CyMgI9vb2EEURUVFRat+oH4uPj8fly5fT/CGmBM+Zupx0zoAPf7G+efMGxYsXx19//YXy5ctn+MRNiuDgYLi5ueHdu3effWw4ODg4w34lSUJMTAzCw8NRpkwZRYtqftxnQkIC9PX107w1AQBz5sxBQkICBg4c+Nnvy4/7ffnyJQwMDGBiYoL379/j1atXarl9HJuUlITIyMhUfzkrPQakXNmyZXHixIl0i4pvZeHChVixYgWio6Pln1GSJMHGxgb9+vWTb3Pt3bsXr169go+PT5r9iKKI/fv3o2PHjpg8eTKuXr2KnTt3pop7//49unTpggMHDmDEiBEoXrw42rVrl2afM2bMwM2bN9X+sAE+/EH0008/YevWrYiOjsbZs2fV/uhLKdxSNGjQQO2PsokTJ+L69ev4/fffP3t8WAQRUbbi4OCA06dPq92m+5axmb3/rBJL2UtERITaHxxfc47TKrY/9rliO8XHBXxaTp8+jbNnz6J3794a/cH6uT84PsaB0Z94+vQpgoKC5IFwT548wdy5czFz5kxcv35dLTY5ORk3btyQLy9/LDExEVu3bs0ysZm9/6wSm5EnT56oza+RlWMze/+ZGfu5W1m6js3s/WeVWMpeihQpAnd3d7i7u8sF0MOHD+Hn56fo/R/HGhgYZHglNCoqStH/9+fPn2PEiBHpttesWRNjxoyBhYWFRrk+e/YMw4cPVxTLIugjoaGhqFChAlq3bo2KFSvi0qVLqF+/PrZu3YrAwEB4enrKI9kfPnyI6tWro1q1aihVqhQ6deoEURTlvl68eCGfsMyOzez9Z5XYz4mOjlb8izqzYzN7/1klloi+3LNnzxT/kaiL2MzeP8CB0WpmzpyJVq1aYebMmfj111/RuXNn1KtXD4sXLwYA+Pn5Ye7cudi8eTOmTp0KlUqF4OBgvHjxAhMmTEDTpk2xZ88etadtAGR6bGbvP6vEnj17Ns3znuLjx2gzOzaz959VYtOyYMGCVI8xf8vYzN5/VomlrO9zhcDHU0joIjaz968ExwR9pEiRIjh06BBcXFzw7t072NjY4MiRI6hYsSIA4PLly+jYsSOuX78OV1dXbN26VX4S4N27d+jduzdu3LiBffv2QZIkebr3zI61trbONrnqMjZlqYSMLvkLgpAlYiVJyja56jKWiL5cgQIF5GVC0pKcnIzExET5/6W2YyVJytT9K/kZwtthH9HVpGSZHZvZ+88qsZpMDpfZsZm9/6wSS0RfTumklbqKzez9K8Ei6CMpcxqkUDIp2cdS5klwcXFRm/cis2Mze/9ZJfbjeTDS+vp4HozMjs3s/WeVWCL6cimTVqbn4yuyuojN7P0rwSLoI2lNSvbxo3tpTUr2qZRJyVImnMsKsZm9/6wS261btwzn4vl4crjMjs3s/WeVWCL6cgMHDkSVKlXSbU+ZtFJXsZm9fyU4JugztDEpWWbH2tnZZZtcdRn7ufOryfdCZsRm9v6zSiwRkbawCPqMrDApGSd8Y2xW2H9WiSUi0hbeDvuMrDApGSd8Y2xW2H9WiSUi0hYWQURERJQrsQj6jKwwKRknfGNsVth/VoklItIWjgkiIiKiXIlXgoiIiChXYhFEREREuRKLICLKFcqUKYN+/fpptc/Tp09DpVLh9OnTWu2XNHPy5EnUqlULtra2UKlUEEURALBz5064u7vDysoq3bnCKHdjEUS5nkqlUvS1efNmrexv3rx52Ldvn+L4d+/eYfXq1ahduzYcHR3h4OCASpUqoW/fvrhw4YJWcspqPj32Dg4OaNq0KQ4dOpQp+Wh6znTt1atX8Pf312nxdfDgQfj4+KBYsWKwsrKCs7Mz2rdvr3gm3k/t2LEDy5Yt03KWH9YP7Nq1K/T09DB79mysXLkSZmZmiIiIQJ8+fWBvb48FCxZg0aJFWt83ZX8GmZ0AUWZbuXKl2utff/0Vf/31F3755Re17RlN066J+fPno2XLlmjevLmi+C5duuDQoUPw9vZGp06dAAD//vsvjh49CicnJ1SuXFkreWU1tWrVQqdOnSBJEh48eIB169ahffv2CAwMRL169b5pLumds+rVq+Px48cwMjL6pvm8fv0as2bNAgDUrFlTq31LkoQhQ4Zgw4YNKFWqFPr06YNChQohNjYWhw8fxo8//ojVq1ejXbt2GvUbGBiI69evo3///lrN959//oEoihg5ciSaNWsmbw8JCcH79+8xbdo0lClTRqv7pJyDRRDlej4+PmqvT5w4gf/973+ptmeG//3vfzhw4ABGjx6NsWPHqrVJkoSnT59+s1ySkpLw/v37b7a0xffff692Dlq2bIkqVapgxYoV37wISo+enh6MjY0zOw2tWrp0KTZs2IDevXtj1qxZ0NP774bBkCFDcPToUbx79y4TM1QXExMDAGpL52S0nehjvB1GpNCOHTtQt25d2NrawsnJCV27dkVERIRazJ07d9CtWze4uLjA2toarq6u+PHHH/H48WMAH27zJCQkYOvWrfKtno//ev3U3bt3AQDVqlVL1SYIQqq5dZ4/f46JEyeiXLlysLa2RokSJdCrVy88evRIjomNjcXgwYNRvHhx2NjYwMPDI9UitPfu3YNKpcKCBQuwatUqVKhQAdbW1ggNDQUAPH78GAMHDkTx4sVhbW0Nd3d3rF27NlWOa9asQbVq1WBnZwdHR0fUqFED69evz+Aop8/FxQUWFhbyMUnx5s0b/Pzzz3KOJUqUwNixY/Hq1asM+3v79i1++ukn1K1bF05OTrC1tYWnp2eq214ZnbNPxwQtWbIEKpUqVY4AMGfOHKhUKty7d0/e9r///Q/t2rWDo6MjbG1t0bhxY5w6dSrDvO/du4fvv/8eADBr1iw5p4/HO129ehXt2rWDg4MD7Ozs0KxZM5w7dy7DfoEPV5jmz58PZ2dn+Pv7qxVAKerXr48mTZoAADZv3pzqM6V1XJo1a4ZDhw7hwYMHarc5P2f37t2oU6cObG1tUbRoUfTs2RMPHjyQ25s1a4YuXboAAFq0aCEfhzJlymDChAkAPqw4rlKp4O/v/9n9Ue7DK0FECixYsADTpk2Dl5cXOnXqBFEUsXr1ajRu3BhnzpyBpaUl3r17h9atWyMxMRG9evWCjY0NoqOjcezYMTx+/Bi2trZYuXIlBg0ahAoVKqBbt24AAGtr63T3mzKYc8eOHahWrRoMDQ3TjU1ISECzZs1w48YNdOzYEeXLl0dcXByOHDmCO3fuwM7ODomJiWjRogVu3bqFXr16oWjRovjzzz8xePBgxMXFYejQoWp9bt++HQkJCejWrRvy5s0LW1tbxMTEoH79+khOTkbPnj1hZWWFkydPYvjw4YiLi8PIkSMBABs3bsSIESPg5eWF3r174927d7h58yZCQkLQvXt3jc/B8+fPIYoiihYtKm+TJAmdO3fG2bNn0aVLF7i6uiIsLAxr167FzZs3sXPnTgiCkGZ/L1++xK+//orWrVujU6dOSExMRGBgIDp37owdO3agQYMGAKDROfP29sakSZOwc+dODB8+XK1t165dqFSpEpycnAAAZ86cQZs2bVCmTBmMHDkShoaG2L59O1q3bo1du3ale5vL0tIS8+fPx7Bhw9C8eXO0aNECAOTjEhYWhqZNm8LU1BQDBw6EsbExNmzYgFatWmHXrl2oXr16usc4JCQEcXFx8PX1hYGB9n49jBgxAi9evMCjR4/w008/KXrP9u3b4evrCzc3N0yaNAmxsbFYuXIlgoODcerUKVhYWGDEiBH4v/buPCaqq+Hj+BcHI4O1iiyxVNORojjiH2CwUgFZrLIpyJJal2oK1NQqiLhvLVVAYo0WQcQdDYZUKIMiCCIIREmaViWyiFKrLV0VBJzYggLz/kHmlpFhe9o8z5tyPgkhuXfm3HPvneT+5mwzbdo0jhw5wvr165k8eTITJ07E19eX7OxsMjMziYuLw9TUFFtb23/sfIR/DxGCBKEf9fX1xMbGsmXLFjZv3ixtDwoKwtHRkeTkZD755BNqa2t5+PAhp0+fxt/fX3qdNhRAV9dbVFQUCoViQN1tDg4OuLi4kJaWRn5+Pi4uLrz11lt4enpiZWWl89qDBw9SVVVFamoqCxculLZv2LBB+m2u1NRUampqSE5OZsmSJQCEhYURGBhIfHw8K1asYOzYsTrnfuPGDcaNGydtW7t2Lc+fP6e8vBwzMzMAQkJCiIiIYP/+/Xz44YeMGTOGgoIClEplj1amgWptbaWxsRGNRsNPP/1ETEwMHR0dOtc2MzOTK1eukJOTg7Ozs7Td3t6elStXcvXqVTw8PPSWP2bMGCorK3W691auXImrqytJSUlSCBrMPRs/fjwzZ87sEYJqa2upqamRAoBGo2HdunU4OjqSnZ0tBbWQkBBmz57N7t27uXz5st5jjBw5En9/f6KiorC1te1Rp927d9Pa2kpJSYnUYrR06VJmzJjB9u3bKSkp6bX+tbW1AP94YHB3d8fS0pLm5uYBfe5fvHjBzp07sbGx4dKlS8jlcgDc3NxYsGABBw4cICYmBnd3d54+fcqRI0dwc3PTCY4PHjwgMzMTX19fKXgKwstEd5gg9CMnJ4f29nYCAwNpbGyU/l599VWmTp0qNfmPGjUKgKKiIp49e/aPHNvAwIAvv/ySbdu2MXr0aFQqFVu3bmX69OkEBQVJ3WwAFy5cQKlU6gSg7uUAXL58GTMzM50HkUwmY9WqVbS1tfV4QPr6+uoEII1Gw/nz55k3bx4GBgY618PDw4M///yTGzduAF1jMX7++Wdu3rz5H517eno6b775JtbW1ri5uVFWVkZkZCSrV6+WXqNSqbC2tkapVOrUxcnJCQMDgz5nT8lkMikAPX/+nKamJtRqNbNmzaKiouI/qjNAYGAg1dXV3Lt3T9qWlZXFsGHDCAgIALq6q+rq6ggODubJkydSvdVqNW5ubnz77bf9dufp09HRQXFxMV5eXlIAAjA1NWXJkiVUVFTw6NGjXt+vVquBvz7L/yu3bt3i0aNHhISESAEIugaB29nZ9RoQBWGwREuQIPTj/v37AL3OwlIoFNL/1atXc+jQIc6dO8fMmTPx8vJi0aJFOq0rg2VsbMymTZvYtGkTjx8/5uuvv+bkyZMUFRUREhJCXl4e0PXN18fHp8+y6uvrsbKyQiaT6Wy3sbEB4Mcff9R7bloNDQ00NzeTlpZGWlqa3mNoB6RGRkZSVlaGh4cHCoUCd3d3AgICmD179oDO29PTk1WrVvHixQtu3rzJ/v37aWtr0xmncv/+ferq6nQe+Prq0pszZ86QnJzM3bt3dX7JvrcutIFYuHAhW7du5auvvpIGs6tUKt5++21ee+01qd4A4eHhhIeH6y3nyZMnGBsbD+rYDQ0N/PHHH0yaNKnHvsmTJwNd97i37jxt+NGGof8V7bif3s7jwoUL/+0qCf9SIgQJQj86OzuBrq4XfeMkus8Oio2NZdmyZVy6dIni4mJ27NjBvn37yM3NZcqUKX+7Lubm5syfP5/58+fj4+NDeXk59fX1TJgw4W+XrU/3b+Hw17UIDg5m2bJlet+jPU8bGxu++eYbCgsLKSoqoqCggFOnThEWFsa+ffv6PbalpSVubm4AzJ07FwsLC9atW4eTk5M0Vb2zs5MpU6YQHx+vt4zurVgvO3fuHBEREXh5ebF27VrMzc0xNDTk7NmzZGRk9Fu/3lhYWODs7Cy12t2+fZu6ujqdgcva6xgdHY2dnZ3ecrRdjf9N2jBcU1MzoCUceguL2vMThP/vRAgShH5oB5yOHz9+QEFGqVSiVCqJioqiqqoKNzc3kpOTOXjwIPD3Whm6mz59OuXl5fz2229MmDCBiRMncufOnT7fM2HCBG7fvk1HR4dOa5C266a/VXXNzMwYNWoU7e3tUkDpi7GxMf7+/vj7+9Pe3s7HH3/M8ePHiYqKwtLSsv+T7Gb58uUcOnSI3bt34+vri4GBARMnTqSiogJXV9dBX9fs7GwUCgXp6ek679W3KOZgyw4KCiIiIoKqqipUKhWGhoY6Y5m0n6lXXnllQNdxoPUxMzPD2NiYurq6Hvu02/q6x46OjowZM4bMzEzWr1/fo8XwZdoZXi0tLTrbX25RHCxtqK+rq+sxpquurk6s/iz8Y8SYIEHoh5+fHzKZjL179+p0mWg1NjYC8PTpU9rb23X22djYIJfLdR4SxsbG0rL+/bl//77eB8rz588pLS1FJpNJXUF+fn7cuXOH7OzsHq/X1tvT05OGhgadlo7Ozk5SUlIYMWJEvw9kmUyGn58fubm5VFZW9tjffd2iJ0+e6OwzNDRk6tSpQM+H5kDIZDLWrFnD3bt3pWnsAQEBPHr0SO/0/La2tj67dbQP+O739OHDh3pXhh7MPYOuezF8+HCysrJQqVS4urpiamoq7bezs8PKyopDhw7prWN/6z9pW+herpNMJmPOnDnk5+frTNNvamoiPT0de3v7PmcjyuVyoqKiuHfvHtu3b9f7eS8uLiY/Px/4K8x1n37f0dGhdzD8yJEjaWlp0Vvmy7T1TE1NpbW1VdpeXl7OrVu38PT07LcMQRgI0RIkCP1QKBRER0ezc+dO6uvr8fX1ZfTo0fzwww/k5eUREBDA1q1bKSsrY+PGjfj5+TFp0iQ0Gg1ZWVmo1WoCAwOl8uzt7SktLSUxMRFLS0vMzMxwdXXVe+yqqipCQ0OZM2cOs2bNwtTUlMePH5OZmUl1dTVr1qyRxhtFRESQk5NDaGgoxcXF2NnZ0dLSQmFhIdu2bcPZ2ZkVK1Zw+vRpwsPDuX37NgqFgtzcXEpLS/n0008HNHYpOjqaa9euMW/ePJYvX45SqaS5uZnKykouXrzI77//DnQFFHNzcxwdHbGwsODBgwccPXoUW1tbqdtlsN577z1iY2M5cOAACxYsYNGiRZw/f54NGzZw/fp1HB0d0Wg0fPfdd6hUKlJTU3udau7t7U1OTg6LFy/G29ubX375hRMnTmBtbd0j4A3mnkFXC4mHhwfHjh1DrVbrzBCErkUWExMTCQ4OxtHRkaVLl/L666/z66+/cv36dTQaTZ8/0yGXy1EqlWRlZWFtbc3YsWN54403cHBwYMeOHVy9ehUvLy/CwsKkKfItLS0DmqkXHh7OvXv3SElJ4dq1ayxcuJBx48bR2NhIUVERZWVlHD9+HOhq9ZwxYwa7du2iqakJExMTsrKyenwZ0F7DrKwstmzZgoODA8OGDSMoKEhvHYYPH86uXbv46KOP8Pb25t1335WmyFtaWhIZGdnveQjCQIgQJAgDEB4eLn1z37dvH52dnVhaWjJ79mxpNta0adN45513KCws5MyZM4wYMQKlUsnZs2d1FkSMi4sjMjKS+Ph4nj17hpOTU68P1FmzZrFz506uXLlCSkoKDQ0NyOVybG1tSUpKkn5GA7q+aefl5bFnzx4uXrxIeno65ubmODk5Sa1FRkZG5OTk8Nlnn5GRkUFLSwtWVlYkJCSwYsWKAV0Lc3NzioqK2Lt3L7m5uZw8eRITExMmT55MTEyM9LoPPviAjIwMDh8+jFqtZty4cSxdupSNGzfqXYRvIIyMjAgLC2PPnj2Ulpbi6upKWloahw8fJj09nby8PIyMjFAoFISGhjJt2rRey1qyZAkNDQ2cOHGCkpISrKysiIuL4/vvv+8RggZzz7QCAwMpKChgxIgResfXODk5UVhYyOeff86JEydQq9VYWFgwffp0aQHAviQmJrJ582Z27NhBW1sbixcvxsHBQZpWvmvXLhISEujs7MTOzo6EhIQ+1wjSMjAwICkpCR8fH06dOsXhw4dpaWnBxMQEBwcH0tPTpcUSAY4dO0ZkZCRffPEFo0eP5v3338fFxaXHLMXQ0FCqq6s5d+4cR48eRaPR9BqCoCvwyuVyDhw4QHR0NHK5nLlz5xIdHa3TqiYIf4dBc3Nz/22TgiAIgiAI/zJiTJAgCIIgCEOSCEGCIAiCIAxJIgQJgiAIgjAkiRAkCIIgCMKQJEKQIAiCIAhDkghBgiAIgiAMSSIECYIgCIIwJIkQJAiCIAjCkCRCkCAIgiAIQ5IIQYIgCIIgDEn/B2rx/ZbiGmLJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 576x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "\n",
    "ax = plt.subplot(2,1,1)\n",
    "sheepskin.plot.bar(x=\"minscore\", y=\"n\", ax=ax)\n",
    "plt.title(\"McCrary Test\")\n",
    "plt.ylabel(\"Smoothness at the Threshold\")\n",
    "\n",
    "ax = plt.subplot(2,1,2, sharex=ax)\n",
    "sheepskin.replace({1877:1977, 1874:2277}).plot.bar(x=\"minscore\", y=\"n\", ax=ax)\n",
    "plt.xlabel(\"Test Scores Relative to Cut off\")\n",
    "plt.ylabel(\"Spike at the Threshold\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "第一个图显示了我们的数据密度如何。 正如我们所见，阈值周围没有尖峰，这意味着没有聚束。 学生们并没有操纵他们可以落在门槛上的哪个地方。 这里仅出于说明目的，第二个图显示了如果学生可以操纵他们落在阈值的位置，那么聚束会是什么样子。 我们会看到刚刚超过阈值的单元格的密度出现峰值，因为许多学生会在那个单元格上，勉强通过考试。\n",
    "\n",
    "解决这个问题，我们可以回过头来估计羊皮效应。 正如我之前所说，Wald 估计器的分子可以像我们在 Sharp RD 中一样进行估计。 在这里，我们将使用带宽为 15 的核函数作为权重。由于我们还有单元格大小，我们将核函数乘以样本大小以获得单元格的最终权重。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "           <td></td>             <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th>          <td> 1.399e+04</td> <td>   83.678</td> <td>  167.181</td> <td> 0.000</td> <td> 1.38e+04</td> <td> 1.42e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>minscore</th>           <td>  181.6636</td> <td>   16.389</td> <td>   11.084</td> <td> 0.000</td> <td>  148.588</td> <td>  214.739</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>threshold</th>          <td>  -97.7571</td> <td>  145.723</td> <td>   -0.671</td> <td> 0.506</td> <td> -391.839</td> <td>  196.325</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>minscore:threshold</th> <td>   18.1955</td> <td>   30.311</td> <td>    0.600</td> <td> 0.552</td> <td>  -42.975</td> <td>   79.366</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.table.SimpleTable'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sheepsking_rdd = sheepskin.assign(threshold=(sheepskin[\"minscore\"]>0).astype(int))\n",
    "model = smf.wls(\"avgearnings~minscore*threshold\",\n",
    "                sheepsking_rdd,\n",
    "                weights=kernel(sheepsking_rdd[\"minscore\"], c=0, h=15)*sheepsking_rdd[\"n\"]).fit()\n",
    "\n",
    "model.summary().tables[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这告诉我们文凭的效果是 -97.7571，但这在统计上并不显着（P 值为 0.5）。 如果我们绘制这些结果，我们会在阈值处得到一条非常连续的线。 受过更多教育的人确实赚了更多的钱，但在他们获得 12 年级文凭的时候并没有飞跃。 这个论据支持这样一种观点，即教育通过提高人们的生产力来增加收入，而不仅仅是通过文凭给出一个信号。 换句话说，没有羊皮效应。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sheepskin.plot.scatter(x=\"minscore\", y=\"avgearnings\", color=\"C0\")\n",
    "sheepskin.assign(predictions=model.fittedvalues).plot(x=\"minscore\", y=\"predictions\", ax=ax, color=\"C1\", figsize=(8,5))\n",
    "plt.xlabel(\"Test Scores Relative to Cutoff\")\n",
    "plt.ylabel(\"Average Earnings\")\n",
    "plt.title(\"Last-chance Exams\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "然而，正如我们从不服从偏差的工作方式中知道的那样，这个结果偏向于零。 为了纠正这个问题，我们需要在第一阶段对其进行缩放并获得 Wald 估计量。 不幸的是，没有一个好的 Python 实现，所以我们必须手动完成并使用自助抽样法来获取标准误。\n",
    "\n",
    "下面的代码运行 Wald 估计器的分子，就像我们之前所做的一样，还通过将目标变量替换为干预变量“receivehsd”来构造分母。 最后一步只是将分子除以分母。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def wald_rdd(data):\n",
    "    weights=kernel(data[\"minscore\"], c=0, h=15)*data[\"n\"]\n",
    "    denominator = smf.wls(\"receivehsd~minscore*threshold\", data, weights=weights).fit()\n",
    "    numerator = smf.wls(\"avgearnings~minscore*threshold\", data, weights=weights).fit()\n",
    "    return numerator.params[\"threshold\"]/denominator.params[\"threshold\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "from joblib import Parallel, delayed \n",
    "\n",
    "np.random.seed(45)\n",
    "bootstrap_sample = 1000\n",
    "ates = Parallel(n_jobs=4)(delayed(wald_rdd)(sheepsking_rdd.sample(frac=1, replace=True))\n",
    "                          for _ in range(bootstrap_sample))\n",
    "ates = np.array(ates)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "使用自助法的样本，我们可以画出ATE的分布，并看到95%置信区间在什么地方。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(ates, kde=False)\n",
    "plt.vlines(np.percentile(ates, 2.5), 0, 100, linestyles=\"dotted\")\n",
    "plt.vlines(np.percentile(ates, 97.5), 0, 100, linestyles=\"dotted\", label=\"95% CI\")\n",
    "plt.title(\"ATE Bootstrap Distribution\")\n",
    "plt.xlim([-10000, 10000])\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如您所见，即使我们按第一阶段缩放效果，它仍然与零没有统计学差异。这意味着教育不是通过简单的羊皮效应来增加收入，而是通过提高一个人的生产力。\n",
    "\n",
    "## 关键思想\n",
    "\n",
    "我们学会了如何利用人为的不连续性来估计因果效应。这个想法是我们将有一些人为的阈值，使干预的概率跳跃。我们看到的一个例子是年龄如何使饮酒的概率在 21 岁时跃升。我们可以用它来估计饮酒对死亡率的影响。我们利用了在非常接近阈值的地方，我们有一些接近随机试验的东西这样一个事实。非常接近阈值的实体可能会采取任何一种方式，而决定它们落在何处基本上是随机的。有了这个，我们可以比较上面和下面的那些，以获得干预效果。我们看到了如何通过使用核函数的加权线性回归来做到这一点，以及这个方法如何自动地为我们的 ATE 提供标准误估计。\n",
    "\n",
    "然后，我们看看在模糊 RD 设计中会发生什么，这里存在不服从的样本点。我们看到可以采用对IV的方式一样来处理这种情况。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
